Proceedings of the IEEE Conference on Decision and Control
Publications in this journal
Conference Proceeding: Stability of high order distributed power control[show abstract] [hide abstract]
ABSTRACT: There are several proposed algorithms for distributed power control of wireless networks. In this article an extended algorithm including high order dynamics is discussed and sufficient conditions for stability are derived. The stability analysis is first made using analysis in linear scale and then with logarithmized variables in a control theoretic approach, using both input-output and Lyapunov theory.Decision and Control, 2009 held jointly with the 2009 28th Chinese Control Conference. CDC/CCC 2009. Proceedings of the 48th IEEE Conference on; 01/2010
Conference Proceeding: The asymmetric sinistral/dextral Markov-Dubins problem[show abstract] [hide abstract]
ABSTRACT: We consider a variation of the classical Markov-Dubins problem dealing with curvature-constrained, shortest paths in the plane with prescribed initial and terminal positions and tangents, when the lower and upper bounds of the curvature are not necessarily equal. The motivation for this problem stems from vehicle navigation applications when the vehicle may be biased in taking turns at a particular direction due to hardware failures or environmental conditions. We employ optimal control to characterize the structure of the shortest path and we resort to geometric techniques to provide sufficient conditions for optimality of the resulting path.Decision and Control, 2009 held jointly with the 2009 28th Chinese Control Conference. CDC/CCC 2009. Proceedings of the 48th IEEE Conference on; 01/2010
Conference Proceeding: Iterative calibration method for inertial and magnetic sensors[show abstract] [hide abstract]
ABSTRACT: We address the problem of three-axis sensor calibration. Our focus is on magnetometers. Usual errors (misalignment, non-orthogonality, scale factors, biases) are accounted for. We consider a method where no specific calibration hardware is required. We solely use the fact that the norm of the sensed field must remain constant irrespective of the sensors orientation. The proposed algorithm is iterative. Its convergence is studied. Experiments conducted with MEMS sensors (magnetometers) stress the relevance of the approach.Decision and Control, 2009 held jointly with the 2009 28th Chinese Control Conference. CDC/CCC 2009. Proceedings of the 48th IEEE Conference on; 01/2010
Conference Proceeding: Receding horizon temporal logic planning for dynamical systems[show abstract] [hide abstract]
ABSTRACT: This paper bridges the advances in computer science and control to allow automatic synthesis of control strategies for complex dynamical systems which are guaranteed, by construction, to satisfy the desired properties even in the presence of adversary. The desired properties are expressed in the language of temporal logic. With its expressive power, a wider class of properties than safety and stability can be specified. The resulting system consists of a discrete planner that plans, in the abstracted discrete domain, a set of transitions of the system to ensure the correct behaviors and a continuous controller that continuously implements the plan. To address the computational difficulties in the synthesis of a discrete planner, we present a receding horizon based scheme for executing finite state automata that essentially reduces the synthesis problem to a set of smaller problems.
Conference Proceeding: Stable inversion-based robust tracking control in DC-DC nonlinear switched converters[show abstract] [hide abstract]
ABSTRACT: This article studies the robust tracking control problem in nonminimum phase DC-DC nonlinear switched power converters. The proposed procedure introduces a stable inversion-based iterative technique that, taking advantage of Banach's fixed point theorem, provides closed-form analytic expressions uniformly convergent to the exact solution of the corresponding inverse problem. Then, piecewise constant load disturbances belonging to an a priori known compact set are successfully rejected by means of dynamic compensation. Simulation results validate the proposal.
Conference Proceeding: An algorithm for estimating time-varying commodity price models[show abstract] [hide abstract]
ABSTRACT: Given the current financial crisis, there is renewed interest in modelling how the price of commodities change in the market. Traditionally, such models have assumed constant parameters. However, large and sudden changes in the parameters can also be anticipated due to market shocks. This paper is aimed at addressing this issue. We first describe a bias-variance trade-off in parameter estimation when sudden changes are considered. We then propose a mechanism to achieve a compromise between the observed bias and variance. A key ingredient of this mechanism is to use an estimator having a variable memory length.
Conference Proceeding: A robust STATCOM control to augment LVRT capability of fixed speed wind turbines[show abstract] [hide abstract]
ABSTRACT: In this paper, we propose an algorithm to design a robust output feedback controller for a static synchronous compensator (STATCOM) to enhance the low-voltage ride-through (LVRT) capability of fixed-speed wind turbines equipped with induction generators. The wind generator is a highly nonlinear system, and in this paper it is modelled as a linear part plus a nonlinear part. The nonlinear part is written as the Cauchy remainder term in Taylor series expansion; this enables us to use the bound of this term in robust control design. Large disturbance simulations demonstrate that the proposed controller enhances voltage stability as well as transient stability of induction generators during low voltage ride through transients and thus enhances the LVRT capability.
Conference Proceeding: A non-adaptive approach to the problem of tracking uncertain oscillations[show abstract] [hide abstract]
ABSTRACT: This paper considers the problem of output regulation for nonlinear, possibly non-minimum phase, systems, in the presence of parameter-uncertain exosystems. The proposed result relies upon a framework recently proposed by the authors to deal with the presence of unstable zero dynamics in nonlinear output regulation. An interesting aspect of the theory presented in the paper is given by the fact that the internal model-based regulator is designed without using adaptation strategies as classically done in the literature on adaptive output regulation. Limits of performance linking the properties of the zero dynamics of the regulated plant and of the exosystem can be obtained as nice byproduct of the result.
Conference Proceeding: Optimal H∞ synchronization of general discrete-time delayed chaotic neural networks via dynamic output feedback[show abstract] [hide abstract]
ABSTRACT: This paper deals with robust H<sub>∞</sub> synchronization of general discrete-time chaotic neural networks with external disturbance. This general discrete-time model, which is the interconnection of a linear delayed dynamic system and a bounded static nonlinear operator, covers not only several well-known discrete-time delayed neural networks, such as Hopfield neural networks, cellular neural networks (CNNs), bidirectional associative memory (BAM) networks, and recurrent multilayer perceptrons (RMLPs), but also Lur'e systems. Based on Lyapunov stability and H<sub>∞</sub> control theories, dynamic output feedback controllers are established to not only guarantee exponentially stable synchronization of both master and slave systems with time delays, but also reduce the effect of external disturbance to an H<sub>∞</sub>-norm constraint. Furthermore, two classes of optimal controllers are presented, one minimizing the H<sub>∞</sub>-norm bound, the other maximizing the exponential synchronization rate. The control design equations are shown to be a set of linear matrix inequality (LMI) standard problems which can be easily solved by various convex optimization algorithms to determine the optimal H<sub>∞</sub> control laws and the optimal exponential synchronization rates.
Conference Proceeding: Stability and robustness conditions using frequency dependent half planes[show abstract] [hide abstract]
ABSTRACT: This paper presents a sufficient condition that establishes closed loop stability for linear time invariant dynamical systems with transfer functions that are analytic in the open right half complex plane. The condition is suitable for analyzing a large class of highly complex, possibly interconnected, systems. The result is based on bounding Nyquist curves by using frequency dependent half planes. It provides (usually non-trivial) robustness guarantees for the provably stable systems and generalizes to the multidimensional case using matrix field of values. Concrete examples illustrate the applications of the condition. From our condition, it is easy to derive a relaxed version of the classical result that the interconnection of a positive real and strictly positive real linear system under feedback is closed loop stable.
Conference Proceeding: Motor planning as an optimization of command representation[show abstract] [hide abstract]
ABSTRACT: A fundamental problem in the field of motor neuroscience is to understand how our brain generates appropriate motor commands for precise movements effortlessly. The problem seems difficult since there are infinitely many possible trajectories and our musculo-skeltal system is generally redundant. We focus on the motor command representation and show that a simple strategy can solve the problem for a planar two-joints arm model. We also discuss the emergence of the muscle synergies, which may enable us to make natural motor behaviors with smaller degrees of freedom.
Conference Proceeding: Two degree of freedom robust optimal control design using a linear matrix inequality optimization[show abstract] [hide abstract]
ABSTRACT: This paper proposes a new method for the control design for reference tracking in a two degree-of-freedom (2DOF) robust optimal control framework. The main contribution of this paper is formulation of 2DOF multi-objective optimal control problem in terms of linear matrix inequalities. The proposed method enables formulating and solving for a larger set of performance specifications than existing conventional 2DOF designs. This method also provides a platform for implementing mixed-norm optimizamixed-norm optimization problemstion problems that model many tracking applications. The theoretical results are corroborated by experiments that apply the proposed control design for a tracking problem on a positioning system.
Conference Proceeding: On optimal Fault Detection of nonlinear systems[show abstract] [hide abstract]
ABSTRACT: This report presents a solution to the problem of optimal residual generation for discrete time nonlinear systems. Sufficient conditions for a (sub-) optimal Fault Detection Filter are derived which simultaneously produce robustness to disturbances and enhances sensitivity to faults. The results are derived for general class of input affine nonlinear systems and then it is also shown that these results reduce to the well known results derived for mixed Â¿-/Â¿<sub>Â¿</sub> fault detection filter for linear discrete time systems.
Conference Proceeding: H2 optimization for systems with adobe input delays: A loop shifting approach[show abstract] [hide abstract]
ABSTRACT: This paper studies the H<sup>2</sup> optimization problem for systems with Adobe input delay. These are systems having only two (possibly vector) input channels: one is delay free and the other is delayed. We present a solution based on the reduction of the problem to an equivalent delay-free problem via simple loop shifting arguments. This results in a solution based on two standard algebraic Riccati equations, which are associated with the delay-free version of the problem. The optimal controller is in the dead-time compensator form. We also derive an explicit and transparent expression for the cost of delay and (in the case when the problem is solvable without the delayed channel) a numerically stable form of the optimal solution, which includes exponentials of Hurwitz matrices only. The approach is readily extendible to more general multiple input / output delay cases.
Conference Proceeding: Sensor-based complementary globally asymptotically stable filters for attitude estimation[show abstract] [hide abstract]
ABSTRACT: This paper presents the design, analysis, and performance evaluation of a new class of globally asymptotically stable filters for attitude estimation. The design is based directly on the sensor measurements as opposed to traditional solutions that resort to parameterizations of the attitude, e.g., Euler angles, quaternions, or rotation matrices, and therefore it does not have problems such as singularities, unwinding phenomena, or topological limitations for achieving global asymptotic stability. The proposed solution includes the estimation of gyros biases, incomplete sensor measurements, systematic tuning procedures, and also allows for the inclusion of frequency weights to model colored noise on the different sensing devices. Finally, and due to the inherent structure, the filters are complementary. Simulation results are included that illustrate the achievable performance in the presence of realistic measurements provided by a low-cost, low-power sensor suite.
Conference Proceeding: Self-tuning weighted measurement fusion Kalman filter based on ARMA innovation model[show abstract] [hide abstract]
ABSTRACT: For the multisensor system with different measurement matrices, correlated measurement noises and unknown noise variances, by correlated method, the online identifiers of the noise variances are obtained. Based on ARMA innovation model, a self-tuning weighted measurement fusion Kalman filter is presented, which avoids Lyapunov and Riccati equations, reduces the computational burden and is suitable for real time application. By dynamic error system analysis (DESA) method, it is rigorously proved that the proposed self-tuning fused Kalman filter converges to the corresponding optimal fused Kalman filter with probability one or in a realization, i.e. it has asymptotical global optimality. A simulation example for a target tracking systems with 3 sensors shows its effectiveness.
Conference Proceeding: Inverse optimal adaptive control of a nonlinear Euler-Lagrange system, part I: Full state feedback[show abstract] [hide abstract]
ABSTRACT: A sufficient condition to solve an optimal control problem is to solve the Hamilton-Jacobi-Bellman (HJB) equation. However, finding a value function that satisfies the HJB equation for a nonlinear system is challenging. Inverse optimal control is an alternative method to solve the nonlinear optimal control problem by circumventing the need to solve the HJB equation. Inverse optimal adaptive control techniques have been developed that can handle structured (i.e., linear in the parameters (LP)) uncertainty for a particular class of nonlinear systems that do not include Euler-Lagrange systems with an uncertain time-varying inertia matrix. In this paper, an inverse optimal adaptive controller is developed to asymptotically minimize a meaningful performance index while the generalized coordinates of a nonlinear Euler-Lagrange system asymptotically track a desired time-varying trajectory despite LP uncertainty. A Lyapunov analysis is provided to examine the stability of the developed optimal controller, and preliminary simulation results illustrate the performance of the controller.
Data provided are for informational purposes only. Although carefully collected, accuracy cannot be guaranteed. The impact factor represents a rough estimation of the journal's impact factor and does not reflect the actual current impact factor. Publisher conditions are provided by RoMEO. Differing provisions from the publisher's actual policy or licence agreement may be applicable.
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