IFAC-PapersOnLine

Published by Elsevier
Online ISSN: 2405-8963
Publications
Identified values for α, E 0 , and E 1 (solid) compared to model parameters (dashed).  
Article
Identification of fractional order systems is considered from an algebraic point of view. It allows for a simultaneous estimation of model parameters and fractional (or integer) orders from input and output data. It is exact in that no approximations are required. Using Mikusinski's operational calculus, algebraic manipulations are performed on the operational representation of the system. The unknown parameters and (fractional) orders are calculated solely from convolutions of known signals. A generalized Voigt model describing a viscoelastic material is used to illustrate the approach.
 
Article
Accurate estimation of parameters is paramount in developing high-fidelity models for complex dynamical systems. Model-based optimal experiment design (OED) approaches enable systematic design of dynamic experiments to generate input-output data sets with high information content for parameter estimation. Standard OED approaches however face two challenges: (i) experiment design under incomplete system information due to unknown true parameters, which usually requires many iterations of OED; (ii) incapability of systematically accounting for the inherent uncertainties of complex systems, which can lead to diminished effectiveness of the designed optimal excitation signal as well as violation of system constraints. This paper presents a robust OED approach for nonlinear systems with arbitrarily-shaped time-invariant probabilistic uncertainties. Polynomial chaos is used for efficient uncertainty propagation. The distinct feature of the robust OED approach is the inclusion of chance constraints to ensure constraint satisfaction in a stochastic setting. The presented approach is demonstrated by optimal experimental design for the JAK-STAT5 signaling pathway that regulates various cellular processes in a biological cell.
 
Article
Can a dynamical system paint masterpieces such as Da Vinci's Mona Lisa or Monet's Water Lilies? Moreover, can this dynamical system be chaotic in the sense that although the trajectories are sensitive to initial conditions, the same painting is created every time? Setting aside the creative aspect of painting a picture, in this work, we develop a novel algorithm to reproduce paintings and photographs. Combining ideas from ergodic theory and control theory, we construct a chaotic dynamical system with predetermined statistical properties. If one makes the spatial distribution of colors in the picture the target distribution, akin to a human, the algorithm first captures large scale features and then goes on to refine small scale features. Beyond reproducing paintings, this approach is expected to have a wide variety of applications such as uncertainty quantification, sampling for efficient inference in scalable machine learning for big data, and developing effective strategies for search and rescue. In particular, our preliminary studies demonstrate that this algorithm provides significant acceleration and higher accuracy than competing methods for Markov Chain Monte Carlo (MCMC).
 
Article
Cyber-Physical Systems (CPS) are notoriously difficult to verify due to the intricate interactions between the cyber and the physical components. To address this difficulty, several researchers have argued that the synthesis paradigm is better suited to ensure the correct operation of CPS than the verification paradigm. The key insight of synthesis is that design should be constrained so that resulting systems are easily verified and, ideally, synthesis algorithms should directly provide a proof of correctness. In this paper we present a Linear Temporal Logic fragment inspired by specifications that frequently occur in control applications where we have a set of modes and corresponding targets to be reached for each mode. The synthesis problem for this fragment is formulated as a mode-target game and we show that these games can be solved in polynomial time by providing two embeddings of mode-target games into Generalized Reactivity(1) (GR(1)) games. While solving GR(1) games requires $O(mnN^2)$ symbolic steps when we have m assumptions, n guarantees, and a game graph with N states, mode-target games can be solved in $O(nN^2)$ symbolic steps when we have n modes and a game graph with N states. These embeddings, however, do not make full use of the specificity of mode-target games. For this reason we investigate in this paper a solution to mode-target games that does not rely on GR(1) embeddings. The resulting algorithm has the same worst case time complexity and we illustrate through experimental results the extent to which it improves upon the algorithms obtained via GR(1) embeddings. In doing so, we highlight the commonalities between mode-target games and GR(1) games while providing additional insight into the solution of GR(1) games.
 
Article
Modeling dynamical systems is important in many disciplines, e.g., control, robotics, or neurotechnology. Commonly the state of these systems is not directly observed, but only available through noisy and potentially high-dimensional observations. In these cases, system identification, i.e., finding the measurement mapping and the transition mapping (system dynamics) in latent space can be challenging. For linear system dynamics and measurement mappings efficient solutions for system identification are available. However, in practical applications, the linearity assumptions does not hold, requiring non-linear system identification techniques. If additionally the observations are high-dimensional (e.g., images), non-linear system identification is inherently hard. To address the problem of non-linear system identification from high-dimensional observations, we combine recent advances in deep learning and system identification. In particular, we jointly learn a low-dimensional embedding of the observation by means of deep auto-encoders and a predictive transition model in this low-dimensional space. We demonstrate that our model enables learning good predictive models of dynamical systems from pixel information only.
 
Article
The control and risk assessment in complex information systems require to take into account extremes arising from nodes with large node degrees. Various sampling techniques like a Page Rank random walk, a Metropolis-Hastings Markov chain and others serve to collect information about the nodes. The paper contributes to the comparison of sampling techniques in complex networks by means of the first hitting time, that is the minimal time required to reach a large node. Both the mean and the distribution of the first hitting time is shown to be determined by the so called extremal index. The latter indicates a dependence measure of extremes and also reflects the cluster structure of the network. The clustering is caused by dependence between nodes and heavy-tailed distributions of their degrees. Based on extreme value theory we estimate the mean and the distribution of the first hitting time and the distribution of node degrees by real data from social networks. We demonstrate the heaviness of the tails of these data using appropriate tools. The same methodology can be applied to other complex networks like peer-to-peer telecommunication systems.
 
Article
Nonsmooth nonconvex optimization problems are considered in infinite dimensional sequence spaces lp with p Є (0,1]. Our starting points are necessary optimality conditions in the form of a complementary system and a monotonically convergent algorithm for a regularized version of the original problem. We propose an algorithm for solving the necessary optimality condition based on a combination of the monotone scheme and an active-set strategy. Numerical results for different test cases are provided, e.g. for optimal control problems and microscopy image reconstruction.
 
Article
In this paper, a Nyquist plot-based method which reduces the conservatism associated with Linear Matrix Inequality (LMI) approximation of ambiguous chance constraints is proposed for the design of robust mechatronic systems. The mechanical plant and controller are redesigned over finite frequencies by shaping the open loop Nyquist plot to avoid an ambiguous chance-constrained robust stability disc. Commonly used graphical constraints such as the sensitivity disc are also included in order to satisfy the performance specifications. Our simulation results using the proposed graphical method achieves a robust stability of 91.8% based on a desired probability tolerance for closed-loop stability of (1 — ε) = 0.70 as compared with LMI approximation, which requires the standard deviation of the parametric uncertainties to be reduced by four times in order to satisfy an identical (1 — ε), and achieves a robust stability of 100%.
 
Article
This paper addresses the coordinated output regulation control problem. Consider a network of agents with associated output equations, where the latter is a function of the state of the agent and a coordination vector. Each agent can access its state, its coordination vector, and the coordination vectors of the neighboring agents. We wish to design a distributed control law that steers the output signals to the origin, while simultaneously driving the coordination vectors of the agents of the network to consensus. The proposed model predictive control scheme builds on a pre-existing auxiliary consensus control law to design a performance index that combines the output regulation objective with the consensus objective. A numerical simulation shows the effectiveness of the proposed scheme to solve the cooperative path following control problem for a network of under-actuated vehicles.
 
Article
One important challenge with networked systems is that communication delays can signi?cantly deteriorate system performance. This paper considers a model-free predictor framework to compensate for communication delays and improve networked system performance, where the term "model-free" indicates that the predictor does not need to know the dynamic equations governing the system. Stability analysis of this predictor is available in the literature; however, ensuring stability does not guarantee a good performance. Understanding when the predictor can perform well and what its limitations are is critical, but the performance characteristics of the predictor are unknown. Hence, this paper aims to ?ll this gap by providing a predictor performance analysis for constant time delays. First, a frequency-domain analysis is performed for the predictor and the relationship between the predictor design parameter, time delay, and steady-state performance is revealed. Fundamental limitations of the predictor at higher frequencies are laid out. Next, this analysis is confirmed on a case study. The case study further allows for testing the transient performance of the predictor in closed-loop with the networked system, and shows that the predictor holds signi?cant potential to alleviate the negative impact of communication delays, even if its higher frequency performance may be limited.
 
Article
The asymptotic stability of boundary controlled port-Hamiltonian systems defined on a 1D spatial domain interconnected to a class of non-linear boundary damping is addressed. It is shown that if the port-Hamiltonian system is approximately observable, then any boundary damping which behaves linear for small velocities asymptotically stabilizes the system.
 
Article
This paper presents a decentralized hybrid control scheme for the motion planning and coordination of teams of mobile agents in known obstacle environments with both convex and non-convex obstacles. A mathematical analysis using tools from switched systems theory is carried out to establish the convergence of the system trajectories under certain modeling assumptions on the surrounding environment. The design resolves a class of deadlock situations arising in earlier work, and allows for a wider class of obstacles (both convex and non-convex) to be considered in the environment. Simulation results demonstrate the efficacy of the algorithm.
 
Flexible beam + mass spring damper systems. 
Article
The stability of an undamped Euler Bernoulli beam connected to non-linear mass spring damper systems is addressed. It is shown that under mild assumptions on the local behaviour of the non-linear springs and dampers the solutions exist and the system is globally asymptotically stable.
 
General teleoperated vehicle setup. The Driver and Vehicle communicate in closed-loop with bilateral delays.
Predictor framework applied to the general teleoperated vehicle setup. The Driver and Vehicle communicate with each other indirectly through the predictors.
Designated track, vehicle and landmarks in the virtual environment.  
Bode plot of (2) with control delay t d1 = 300 ms for various λ values within stability region. Predictors can reduce coupling errors for frequencies less than 0.4 Hz.
Amplitude spectrum of throttle (T h), brake (Br) and steering (St) commands at various frequencies. The significant components of all signals are in the low frequency domain where predictors can attenuate coupling errors.
Article
A teleoperated vehicle is a vehicle operated by a human from a distance by means of a communication network. One important challenge with teleoperated vehicles is that communication delays in the network can negatively affect the mobility performance of the vehicle. This paper adopts and further develops a model-free predictor framework to compensate for communication delays and improve vehicle mobility where the term “model-free” indicates that the predictor does not need to know the dynamic equations governing the system. This framework has previously been conceived and applied to the teleoperated vehicle domain; however, prior evaluations have been conducted with simulated drivers and for only the speed control of the vehicle. The contribution of this paper is two-fold. First, the framework is further developed to improve the transient response of the predictors by including a saturation and resetting scheme. Second, to evaluate the effectiveness of the predictor framework with human drivers and combined speed and steering control, a human-in-the-loop simulation platform is developed to emulate a driving task in a virtual environment. Using this platform, human-in-the-loop experiments are performed, where humans are tasked with driving a typical military truck as fast as possible while keeping it as close as possible to the center of the track. Three types of experiments are conducted: (1) without communication delays as a benchmark; (2) with communication delays, but without the predictor framework to quantify the mobility performance degradation due to delays; and (3) with communication delays and the predictor framework to evaluate the change in mobility performance due to the predictor framework. Three metrics are used to quantify performance; namely, track completion time and track keeping error are used to quantify the speed and lateral control performance, respectively, and the steering control effort is monitored to assess drivability. Five drivers repeated each type of experiment seven times, and Analysis of Variance (ANOVA) is used to statistically analyze the results. The conclusion is that the predictor framework improves the mobility performance of the vehicle and increases drivability significantly.
 
Article
Energy based approaches have proven to be specially well suited for the modeling and control of mechanical systems. Among these approaches the port-Hamiltonian framework presents interesting properties for the structural modeling of complex systems and for the design of non-linear controllers using passivity In this paper we use this framework to model a typical micro-robotic contact scenario and to propose a simple but effective globally stabilizing controller. The model and the controller take into account the transitions from a non-contact to a contact state (and the inverse) by the introduction of a non-linear (switching) contact element. A one degree of freedom experimental micro-robotic setup is used to test and illustrate the results.
 
Article
Modeling mobile robot driving performance is a challenging task, but a simple, accurate model can be helpful in making robot system design decisions that balance cost and performance. Driving performance can depend on a variety of factors including human ability, capabilities of the physical robot, and characteristics of the robot's environment (e.g. obstacles, terrain). This paper investigates teleoperated robot driving time for a task that includes obstacles in an environment. We hypothesize that a model analogous to Fitts’ Law can be used to describe robot performance (driving time) as a function of environment difficulty. A new definition of the difficulty index (ID) in Fitts' Law is proposed in this paper that describes an environment's difficulty based on the arrangement of obstacles. The model is tested with data from a human subject study we conducted, in which a simulated differential drive robot was teleoperated through different environments in a manual control mode and semi-autonomous mode (obstacle avoidance). We demonstrate that the model for driving time and our proposed environment difficulty index fit human subject data well for a simple driving task between one pair of obstacles. Additionally, the model is expanded to predict driving time in a more complex environment with multiple pairs of obstacles. The results of this paper provide a building block for predicting teleoperated driving time performance in larger, more complex environments.
 
The DAG in this figure is the derived graph of the dependency graph shown on the left of Fig. 1. The two nodes v 7 and v 4 (marked in red) form a statecontrolling set. The values of all nodes at time t are expressed in their control expression form.
Article
A Boolean network is a discrete-time finite state dynamical system, whose variables take values from the binary set {0,1}, and the value update rules are Boolean functions. A conjunctive Boolean network is a special type of Boolean network, whose value update rule for each variable is comprised only of “AND” operations. Recently there have been extensive investigations on conjunctive Boolean networks. Questions about asymptotic behaviors, stabilities of periodic orbits, and reachability and observability have all been addressed to some extent. We focus in this paper on controllability of a conjunctive Boolean network. Specifically, assuming that there is a selected subset of variables whose values are determined by external control inputs, we pose and answer the question of whether (and how) one can steer the system from any initial state to any final state. We establish a necessary and sufficient condition, via a graphical approach, for a conjunctive Boolean network to be controllable. An explicit control law is also presented along the analysis.
 
Article
We present a variational formulation for nonequilibrium thermodynamics which extends the Hamilton principle of mechanics to include irreversible processes. The variational formulation is based on the introduction of the concept of thermodynamic displacement. This concept makes possible the definition of a nonlinear nonholonomic constraint given by the expression of the entropy production associated to the irreversible processes involved, to which is naturally associated a variational constraint to be used in the variational formulation. We consider both discrete (i.e., finite dimensional) and continuum systems and illustrate the variational formulation with the example of the piston problem and the heat conducting viscous fluid.
 
The availability function in the isothermal case 
Article
This paper is concerned with the stabilization of tubular reactors in which convection, dispersion, conduction phenomena as well as chemical reaction take place. The stabilization is performed by using a Lyapunov function derived from the second law of thermodynamics called availability function. This function is used to design a stabilizing distributed control law around a stationary profile of a tubular reactor driven far from the thermodynamic equilibrium. A numerical example illustrates the proposed control strategy.
 
Article
In this paper, it is shown that the evolution equations for nonequilibrium thermodynamics admit an intrinsic formulation in terms of Dirac structures, both on the Lagrangian and the Hamiltonian settings. The Dirac structures are constructed on the Pontryagin bundle P = TQ ⊕ T⁎Q, where Q = Q × ℝ is the thermodynamic configuration manifold. In particular, it is illustrated how one can develop Dirac structures that include nonlinear nonholonomic constraints originated from the entropy production in each irreversible process. Lastly, we also present the induced Dirac structure on N = T⁎Q × ℝ together with the associated Lagrange-Dirac and Hamilton-Dirac dynamical formulations in analogy with nonholonomic mechanics.
 
Article
In order to understand a series of pressure leaf filters located in the downstream line of a bio-based production site, historical process data have been analysed. In general, changing raw materials induce variability into the pressure profiles and thereby cycle durations of the manually reinitialised dead-end filtrations. The absence of a true steady state results in uncertainty about the optimal way of running the filters, and staff members alter the operational specifications frequently. It appears that, in some cases, this propagates disturbances rather than ameliorate them. Statistical analyses are carried out to illustrate the current situation and especially allow quantifying the extent of the uncertainties. Furthermore, significant correlations between process variables are revealed and economically motivated operational objectives are identified. Secondly, working towards on-line predictions of filtration performance, a model is presented. It is based on classical filtration theory and requires only commonly available measurements (pressure, flow, viscosity). The generated predictions are found to be acceptable for many cycles, but in some cases fail due to non-modelled effects, motivating further work.
 
Article
This paper deals with a payload optimization problem for three-stage space launcher. The mission of the launch vehicle is to put the payload on a sun-synchronous (SSO) orbit. The considered flight sequence includes two boosts. The first one steers the launcher to a transfer orbit. Then, after a ballistic flight, a second boost is used to perform the orbit transfer manoeuvre to inject the payload to the targeted SSO orbit. The optimization method presented here is based on the Hamilton-Jacobi-Bellman (HJB) approach for hybrid dynamical systems.
 
Article
Recently, a new model describing the cell dynamics in hematopoiesis was proposed. It can be described as a delay differential-difference model. Under some conditions on the biological parameters, it admits two equilibrium points. The first one is the O-equilibrium and the second one, which does not always exist, is a strictly positive point. We propose a Lyapunov functional construction in order to investigate the stability properties of both equilibria. For the 0 equilibrium, we establish the global exponential stability when the positive equilibrium does not exist. For the positive equilibrium, we establish its local exponential stability, estimate the decay rate of solutions and provide a subset of its basin of attraction.
 
Article
This paper deals with the extension to sampled-data stabilization of strict feedback dynamics of the Immersion and Invariance procedure proposed in Astolfi and Ortega [2003]. A direct digital approach is developed in two steps: first the target dynamics and immersion mapping are defined for the equivalent discrete-time model; then the control law is built to drive the dynamics towards the invariant manifold. A simulated example illustrates the performances.
 
Article
The primary goal of this paper is to predict fasting glucose levels in type 2 diabetes (T2D) in long-acting insulin treatment. The paper presents a model for simulating insulin-glucose dynamics in T2D patients. The model combines a physiological model of type 1 diabetes (T1D) and an endogenous insulin production model in T2D. We include a review of sources of variance in fasting glucose values in long-acting insulin treatment, with respect to dose guidance algorithms. We use the model to simulate fasting glucose levels in T2D long-acting insulin treatment and compare the results with clinical trial results where a dose guidance algorithm was used. We investigate sources of variance and through simulations evaluate the contribution of adherence to variance and dose guidance quality. The results suggest that the model for simulation of T2D patients is sufficient for simulating fasting glucose levels during titration in a clinical trial. Adherence to insulin injections plays an important role considering variance in fasting glucose. For adherence levels 100%, 70% and 50%, the coefficient of variation of simulated fasting glucose levels were similar to observed variances in insulin treatment. The dose guidance algorithm suggested too large doses in 0.0%, 5.3% and 24.4% of cases, respectively. Adherence to treatment is an important source of variance in long-acting insulin titration.
 
Article
Reaching the maximum yield of produced stainless flat products is an important aim to be successful in the competitive market. This paper describes a solution to optimise the allocation of orders to coils taking into account the actual product quality as well as the quality expected by the customer. In opposite to already available solutions also the appearance of over-quality products is taken into account. Especially for high quality stainless flat products the re-allocation of over-quality products to orders with higher demands can increase the added value distinctly. Another topic is the processing of Manufacturing Specifications (MS). A concept for the digitization of usually freely formulated MS is presented as well as a systematic monitoring, if the MS are really considered by the plant operators. The shown use cases were implemented at the German sites of Outokumpu Oyj, the Finnish producer of stainless flat products sited in Espoo.
 
Article
In this work, we design the sampling policy in sampled-data systems. It is known that implementing such systems using variable sampling periods, instead of a constant period, is more efficient in terms of performance and resource utilization. Thus, after rewriting the system in the framework of impulsive linear systems, a self-triggered control strategy obtained using reachability analysis is proposed in order to define the sampling period as a function of the state.
 
Article
Outdoor microalgae cultures can undergo a photoinhibitory process that can result in a loss in biomass productivity. This loss can be reduced by shading the culture such that the incident photon flux decreases. Based on a simple model of light-limited growth, we look for a control strategy to shadow the culture in order to maximize the biomass productivity. The strategy results in a feedback control that depends on the microalgae strain, the microalgae concentration, and the incident light. In the case that the incident light and the loss rate vary periodically in time, we give conditions for the existence of a positive periodic solution that is globally stable. We show the performance of the feedback control by means of numerical simulations.
 
Article
Microalgae have recently attracted attention for their potential to produce high added compounds, proteins, and even biofuels. Our paper seeks to develop a control strategy for light-limited continuous culture imposing a stress for which microalgae have to adapt. This operating mode - called photoinhibistat - consists, for a culture with a constant dilution rate, in varying the incident light in order to regulate the light at the bottom of the reactor, inducing a light stress. Based on a simple model of light-limited growth, we analyze the dynamics of the photoinhibistat in monoculture and in competition. It appears that the photoinhibistat can be used to select, from the initial microalgae population, the strain with the highest resistance to photoinhibition.
 
Article
In this paper, the problem of dynamical effects of ground irregularity or stability of vehicles in off-road conditions is addressed thanks to a dynamic analysis of the vehicle. In particular, the choice of suitable real-time values for the stiffness and the damping of adjustable suspensions, in order to reduce dynamical effects, is investigated thanks to the analysis of a Laplace transfer function describing the mechanical behaviour of the vehicle. Moreover, a decoupled load transfer computation to identify the suspended masses on each suspension is used and a way to modify in real time suspension parameters by modifying the settling time value in order to drive over obstacles is proposed. This new point of view may permit to use effectively adjustable suspensions in off-road context. Previous approaches indeed only focus on the control of adjustable suspensions on road or by using an actuator in parallel of the suspension and are often dedicated to the driver comfort.
 
Article
The windup phenomenon is interpreted as a consequence of the convergent property absence for system with a saturation. This makes it possible to use the frequency-domain criterion for analysis of anti-windup augmentation in the case of stable and marginally stable plants. Based on this approach, robustness of the systems with respect to time delay in the anti-windup loop is examined and the approach for an optimal choice of the static anti-windup gain is proposed. An application of the convergence-based anti-windup control strategy to aircraft flight control for the case of time-delay in the anti-windup loop is described and studied by simulations.
 
Article
The paper provides an overview of some key contributions to the theory of optimal control performed by V.A. Yakubovich, with the focus on the fundamental findings in linearquadratic optimal regulation and entailed developments in global nonconvex optimization. Along with the works of V.A. Yakubovich, the paper broadly reports on relevant findings of his collaborators, especially in the area of nonconvex global optimization.
 
Article
Several nonholonomic Dubins-car like robots travel over paths with bounded curvatures in a plane that contains an a priori unknown region. The robots are anonymous to one another and do not use communication facilities. Any of them has access to the current distance to the region and can determine the relative positions and orientations of the companion robots within a finite and given visibility range. We present a distributed navigation and guidance strategy under which every robot autonomously converges to the desired distance to the region with always respecting a given safety margin, the robots do not collide with one another, and the entire team ultimately sweeps over the respective equidistant curve at a speed exceeding a given threshold, thus forming a kind of a sweeping barrier at the perimeter of the region. Mathematically rigorous justification of the proposed strategy is offered; its effectiveness is confirmed by extensive computer simulations.
 
Article
A generic time-invariant polling system is modeled as a deterministic hybrid dynamical system in the form of a fluid fabrication facility. The system consists of finitely many infinite size buffers receiving constant-rate inflows from outside the system and a single source of service (finite capacity server). The server can withdraw the buffer’s content but is able to serve at most one buffer at a time, and has to switch among them from time to time, with any switch consuming a nonzero switch-over period. With respect to the long-run maximal scaled wip (work in progress) performance metric, sufficiency of periodic control protocols is established: It is shown that the deepest optimum (that is over all processes in the system, irrespective of their genesis, initial state, and features) is furnished by such a protocol with as high precision as desired. Moreover, sufficiency of special periodic control protocols is established. These protocols prescribe to serve any buffer at the maximal rate until its size reduces to a pre-specified percent of its initial size at the beginning of the visit. This percent is set to be zero for any buffer such that its service at the maximal rate implies reduction of the scaled wip. This is related to another result of the paper that shows optimality of the exhaustive policy for such buffers.
 
Article
The paper deals with observation of nonlinear and deterministic, though maybe chaotic, discrete-time systems via finite capacity communication channels. We consider various types of observability, and offer new tractable analytical techniques for both upper and lower estimation of the threshold that separates data rates for which reliable state observation is and is not possible, respectively. The main results are illustrated via their application to two celebrated samples of chaotic systems associated with the logistic and Lozi maps, respectively. In these cases, the thresholds attributed to some of the considered notions of observability are found in a closed form; they are shown to continuously depend on the parameters of the Lozi system.
 
Article
In the paper the switched GNSS-Estimator navigation system, recently proposed by the authors, is described and numerically studied in the framework of evaluation of the overall UAV control system accuracy.
 
Article
A group of targets moves in 3D in an unknown way. This group should be localized, approached, and circumnavigated by a nonholonomic under-actuated mobile robot. The robot measures only the distances to the targets and also has access to a certain space direction, along with its own coordinate (called “altitude”) along it. A novel navigation law is presented that guides the robot to the locus of space points at a desired root mean square distance from the targets and then ensures repeatedly sweeping over the part of this locus between given lower and upper “altitudes”. This law is reactive, i.e., it converts the current observations into current control in a reflex-like fashion. The proposed navigation approach is rigorously justified by a global convergence result; its performance is confirmed by computer simulation tests.
 
Article
This study is mainly concerned with the problem of robust stabilization of neural networks with two additive time-varying delays via Wirtinger-based double integral inequality. The main purpose of this paper is to design a memoryless state feedback controller which ensuring that the global asymptotic stability of closed loop system. By constructing a suitable Lyapunov-Krosovskii functionals, utilizing Wirtinger-based double integral inequality, the sufficient criteria are derived in terms of linear matrix inequalities technique which ensuring the global asymptotic stability of the proposed neural networks with norm bounded uncertainties. The desired controllers can be calculated by solving the linear matrix inequalities with the help of some standard numerical packages. Finally, the numerical examples are given to demonstrate the effectiveness of the theoretical results.
 
Article
The problem of fault diagnosis in engineering systems with uncertainties described by nonlinear discrete-time models is studied within the scope of analytical redundancy concept. Solution of the problem assumes the checking redundancy relations existing among system inputs and outputs measured over a finite time window. The non-parametric method is considered to construct redundancy relations involving transformation of initial system model into canonical form with the special properties. The obtained results are illustrated by the general electric servoactuator of manipulation robots.
 
Article
In the paper an output control approach for quad copters under the condition of the bounded input signal is presented. This algorithm is based on the high-gain principle "consecutive compensator", which was augmented by an auxiliary integral loop in order to implement the anti-windup scheme. The mathematical model describing quadcopters is decomposed on two parts: a static MIMO transformation and six SISO dynamical channels. The controller generates virtual input signals for these channels, which after inverse MIMO transformation are allocated between the actuators as real bounded control signals.
 
Article
Generalization of PID controllers depending on the plant relative degree is addressed in the paper. The consecutive compensator approach is redesigned in the state-space representation and augmented with the integral loop and anti-windup scheme. The stability of the closed-loop system is proved. Efficiency of the proposed approach is illustrated by the experiments carried out using the 2-DOF indoor quadcopter testbed.
 
Article
This paper proposes a data transfer rate control approach to ensure a prescribed delay in the time critical communication channels of the networked teleoperation systems. The proposed method assumes an active queue management mechanism in the communication link between the master and slave side of the teleoperation system. To handle the nonlinearities in the system model and the extraneous data flow rates in the same communication medium a nonlinear PI control law is designed which controls the video transfer rate from the master side to the slave side of the teleoperation system. The parameters of the control algorithm were determined by applying the State Dependent Riccati Equation approach. Using steady state analysis the maximum rate of the disturbance traffic which can be compensated by control is determined. Simulation measurements were performed to show that the proposed control approach can assure the prescribed delay in the presence of different type of data traffic.
 
Article
We study stability issues for linear two-dimensional (2D) discrete systems by means of the constructive algebraic analysis approach to linear systems theory. We provide a general definition of structural stability for linear 2D discrete systems which coincides with the existing definitions in the particular cases of the classical Roesser and Fornasini-Marchesini models. We then study the preservation of this structural stability by equivalence transformations. Finally, using the same framework, we consider the stabilization problem for equivalent linear systems.
 
Article
In this paper, we revisit the notions of structural stability and asymptotic stability that are often considered as equivalent in the field of multidimensional systems. We illustrate that the equivalence between asymptotic and structural stability depends on where we define the boundary conditions. More precisely, we show that structural stability implies asymptotic stability when the boundary conditions are imposed on the positive axes. But a carefully designed counterexample shows that the opposite does not hold in this case. This illustrates once again the importance of the boundary conditions when dealing with multidimensional systems.
 
Article
Piecewise affine models often provide a good approximation to describe continuous systems, but may involve a high degree of simplification. To compare solutions of the continuous and piecewise affine models, it is important to quantify the differences between solutions in each region of the state space. As an approach, we will use enveloping "bands" to characterize continuous activation or inhibition functions, and then describe the differences between continuous and piecewise affine solutions in terms of the width δ of these bands. As a case study, we will consider the negative feedback loop, a classical motif in two dimensions which results in oscillating behaviour. For this example, it is shown that the two types of models may differ only on a compact invariant set (the interior of a limit cycle), whose diameter is a function of the band width δ.
 
Article
This paper deals with the use of control theoretical concepts in the context of private communication. It is proposed a new and systematic methodology to design a cryptographic architecture belonging to the special class of ciphers called Self Synchronizing Stream Ciphers (SSSC). Till now, the constructions of SSSC were based on automata with finite input memory involving shifts or triangular functions (T-functions) as state transition functions. Besides, only ad-hoc approaches were available in the literature. The contribution of this paper is to propose not only a general framework to design SSSC, but with potentially more general state transition functions as well. Two control-theoretical issues are treated to this end: as a new paradigm, the construction of flat dynamical systems, and on the other hand, the notion of mortality of a set of matrices, a problem which is in general not decidable.
 
Article
The paper deals with dead-beat stabilizability of autonomous switched linear discrete-time systems. More precisely, it is investigated with the problem of finding a condition on the sequences of switches which guarantee that the state of the system reaches the origin in finite steps. A literature overview highlights the fact that such a problem is an open problem in the general case. First, we give necessary and sufficient conditions under which such an autonomous switched linear discrete-time system is dead-beat stabilizable. Then, an algorithm is proposed for deciding when such a sequence exists and for providing the sequence. It is shown that the complexity of the test can be much lower than the exhaustive search.
 
Article
In a supply chain, two essential problems are the production and the distribution. These two problems used to be solved separately, but it is well known that considering them jointly may lead to a global optimization of the supply chain performances. In this paper, we incorporate the delivery plan of a vehicle into a single machine scheduling problem, representing a single manufacturing facility. We consider the simplified case where there is only one vehicle available to serve the customers, with infinite capacity. However, we assume that the data are known with uncertainty. The objective is to find a schedule and a delivery plan so that a robustness criteria is minimized, under a scenario-based uncertainty modeling. In contrast with standard robust optimization approaches for scheduling, we do not propose a single complete solution to the problem that has to be feasible w.r.t. all scenarios and minimizes a worst-case criterion over the scenarios. Instead, we adopt the recoverable robustness framework that considers first-stage decisions and second-stage recovery options. We propose for the first-stage a set of solutions by using the concept of groups of permutable jobs. At second stage, a greedy and online recovery algorithm exploits the revealed information about the jobs available to be scheduled or to be delivered at decision time. We propose two tabu search algorithms, one based on the standard robust optimization scheme and one based on the new approach. We compare the two robust heuristics on a set of randomly generated problem instances.
 
Top-cited authors
Wilfried Sihn
  • Fraunhofer Austria Research GmbH
Matthias Karner
George Lo
  • Siemens Corp
Detlef Zühlke
  • smartfactory-KL