A mathematical model has been developed and used to simulate the controlled thermal performance of a large guarded hot-plate apparatus. This highly specialized apparatus comprises three interdependent components whose temperatures are closely controlled in order to measure the thermal conductivity of insulation materials. The simulation model was used to investigate control strategies and derive controller gain parameters that are directly transferable to the actual instrument. The simulations take orders-of-magnitude less time to carry out when compared to traditional tuning methods based on operating the actual apparatus. The control system consists primarily of a PC-based PID control algorithm that regulates the output voltage of programmable power amplifiers. Feedback parameters in the form of controller gains are required for the three heating circuits. An objective is to determine an improved set of gains that meet temperature control criteria for testing insulation materials of interest. The analytical model is based on aggregated thermal capacity representations of the primary components and includes the same control algorithm as used in the actual hot-plate apparatus. The model, accounting for both thermal characteristics and temperature control, was validated by comparisons with test data. The tuning methodology used with the simulation model is described and results are presented. The resulting control algorithm and gain parameters have been used in the actual apparatus without modification during several years of testing materials over wide ranges of thermal conductivity, thickness, and insulation resistance values.
This paper presents a technique and the means for testing PLC-based control software outside the actual plant environment with the purpose of increasing the confidence level on the compliance of the software to functional and temporal requirements. The need to obtain a high confidence level on the correct software operation arises from the fact that in most of the cases it is quite dangerous and expensive to test unproved PLC operation by linking it with the actual facilities that it is going to control. The proposed technique relies on a combined simulation of the controlled plant and the PLC system and an analysis of the plant responses. The PLC system simulation imitates the way software is executed on a PLC that is programmed in the languages of the IEC1131-3 standard. It is based on the programming model of the IEC standard and analytical formulae for estimating the program runtime. The simulation of the plant is based on a discrete convolution model that is solved at the same rate with the rate determined by the control algorithms. A tool realizing these concepts has been developed and its use in testing the control software of three critical outputs of a distillation column is demonstrated.
This paper highlights some issues related to parameter selection of controller as well as converter circuit and some shortcomings in derivation process of A-HCC, which is used as input to
proposed A-F-HCC . Additionally, the control problem of a
shunt APF is two fold, i.e. effective compensation of harmonics
and reactive power along with efficient regulation of dc link
voltage. However, it seems that the authors in  have ignored
the issue of good dynamic response and dc link voltage is allowed
to go beyond 200% of its reference value. All these issues require a
clarification from the authors of .
In this note, we demonstrate that the stability analysis in the main theorem of the paper [Lin T-C, Kuo C-H. H(∞) synchronization of uncertain fractional order chaotic systems: adaptive fuzzy approach. ISA Trans 2011;50:548-56] is wrong.
We present a simple, low cost but fast 3D shape measurement method. There is no limitation on the object's material and texture. We use a projector to project a strip shifting pattern on the object, and a digital camera to record videos of the scene. The distortion of the strip shadow on the object is used to get the object's 3D information. A novel space-time edge finding method is introduced to position the shadow edge accurately. This edge finding method overcomes the effect of inter-reflection and high light. Using this space-time information, we can calculate the pixels' 3D coordinates. To get the 3D shape of an object with black texture, we improve the black strip pattern to a 3-color strip pattern. The bad data are filtered by a post-processing 3D filter, which makes full use of the neighborhoods' geometric constraints and the view point constraint. Meanwhile, our measurement method is fast, regardless of the complexity of the shape.
Based on the theory of electromagnetic induction flow measurement, the Laplace equation in a complicated three-dimensional (3D) domain is solved by an alternating method. Virtual current potentials are obtained for an electromagnetic flow meter with one spherical bubble inside. The solutions are used to investigate the effects of bubble size and bubble position on the virtual current. Comparisons are done among the cases of 2D and 3D models, and of point electrode and large electrode. The results show that the 2D model overestimates the effect, while large electrodes are least sensitive to the bubble. This paper offers fundamentals for the study of the behavior of an electromagnetic flow meter in multiphase flow. For application, the results provide a possible way to estimate errors of the flow meter caused by multiphase flow.
Minimizing the integral squared error (ISE) criterion to get the optimal controller parameters results in a PD controller for integrating processes. The PD controller gives good servo response but fails to reject the load disturbances. In this paper, it is shown that satisfactory closed loop performances for a class of integrating processes are obtained if the ISE criterion is minimized with the constraint that the slope of the Nyquist curve has a specified value at the gain crossover frequency. Guidelines are provided for selecting the gain crossover frequency and the slope of the Nyquist curve. The proposed method is compared with some of the existing methods to control integrating plant transfer functions and in the examples taken it always gave better results for the load disturbance rejection whilst maintaining satisfactory setpoint response. For ease of use, analytical expressions correlating the controller parameters to plant model parameters are also given.
Optimum coordination of individual brakes and front/rear steering subsystems is presented. The integrated control strategy consists of three modules. A coordinated high-level control determines the body forces/moment required to achieve vehicle motion objectives. The body forces/moment are allocated to braking and steering subsystems through an intermediate unit, which integrates available subsystems based on phase plane notion in an optimal manner. To this end, an optimization problem including several equality and inequality constraints is defined and solved analytically, such that a real-time implementation can be realized without the use of numeric optimization software. A low-level slip-ratio controller works to generate the desired longitudinal forces at small longitudinal slip-ratios, while averting wheel locking at large slip-ratios. The efficiency of the suggested approach is demonstrated through computer simulations.
The application of batch profile characterization tools to enhance process understanding by uncovering the signature of the primary disturbances on the profiles and its effect on the product quality is illustrated on a nylon-6,6 process. The historical profile data for the fixed recipe operation are systematically studied to understand the primary disturbances affecting the process, and it is shown that good online predictions of the final product quality are possible much before the completion of the batch from the available measurement profiles. A simple online recipe adjustment strategy based on the predicted quality deviation from the target is proposed. Results show that the recipe adjustments significantly reduce the variation in the final product quality. Issues in the use of empirical prediction models from recipe-based data are discussed.
A variety of fieldbus technologies and digital fieldbus devices have been introduced within the process industries over the last ten years. There has been a gradual acceptance of the fact that a variety of communication technologies are needed to fully address the application requirements of a manufacturing facility. However, engineers responsible for the specification, engineering, and implementation of control systems require that a common interface and functionality be provided in the control system. This capability should be independent of the underlying fieldbus technology or manufacturer of the fieldbus device. The draft IEC 61804 standard defines how a control system can be structured to provide this flexibility in the utilization of fieldbus technology. In this paper, we discuss how a consistent function block capability may be provided for all fieldbus technology utilized in a control system. Examples will be given of how this standard has been applied in modern control systems to give a consistent interface to Foundation Fieldbus and PROFIBUS. Some detail will be presented on the standard means that is defined for manufacturers to describe function block capability of a field device. An analysis is given of the impact and benefit that the IEC 61804 standard will have on the process industry and on manufacturers of control systems.
The control systems of the NASA 70-m antennas include the antenna control system, the Master Equatorial (ME) control system, and their combinations (called modes). The Master Equatorial is a small telescope mounted on the top of a tower located inside the antenna structure. In the Antenna Encoder mode antenna encoders are used to close the feedback loop. In the Autocollimator mode the Master Equatorial is a master that follows a target, and the antenna is a slave that follows the Master Equatorial. In the Master Equatorial Encoder mode the "master-slave" relationship is reversed. In the paper the analysis begins with the description of the open-loop models of the antenna and of the Master Equatorial. We obtained the models by using field test data and system identification techniques. Next, we analyzed and evaluated the performance of the three modes of the antenna control system. The analysis showed that the Autocollimator and Master Equatorial Encoder tracking modes are feasible for high-rate tracking, and that the latter mode has the smallest tracking error. Finally, we analyzed the switching between antenna modes, necessary while tracking near the keyhold. We showed that switching causes jerks of magnitudes within the acceptable threshold. The contribution of this paper includes the development of the antenna model using field data and system identification procedures, the development of the LQG control algorithm for the 70-meter antenna, the development of two control cooperating systems (antenna and ME), identifying the more appropriate, and analyzing of switching between the two control systems.
Two-stage winged space access vehicles consisting of a carrier stage with airbreathing turbo/ram jet engines and a rocket propelled orbital stage which may significantly reduce space transport costs and have additional advantages offer a great potential for mission safety improvements. Formulating the nominal mission and abort scenarios caused by engine malfunctions as an optimal control problem allows full exploitation of safety capabilities. The shaping of the nominal mission has a significant impact on the prospective safety. For this purpose, most relevant mission aborts are considered together with the nominal mission, treating them as an optimization problem of branched trajectories where the branching point is not fixed. The applied procedure yields a safety improved nominal trajectory, showing the feasibility of the included mission aborts with minimum payload penalty. The other mission aborts can be separately treated, with the initial condition given by the state of the nominal trajectory at the time when a failure occurs. A mission abort plan is set up, covering all emergency scenarios.
The primary objective of fault detection is to detect abrupt undesirable changes in a process at an early stage. This early detection has a potential of preventing loss of production and equipment damage due to these undesirable changes, thus reducing process downtime. This paper details the implementation of some parametric fault detection techniques for sensor decalibration monitoring. A parametric fault detection approach that is handled in depth in this paper is the local approach. This approach developed by Benveniste, Basseville, and Moustakides [Benveniste, A., Basseville, M., and Moustakides, G., The asymptotic local approach to change detection and model validation. IEEE Trans. Autom. Control AC-32 (7), 583-592 (1987)] offers a computationally inexpensive way to attain the objective of monitoring changes in model parameters. However, the algorithm in its original formulation is not applicable to certain processes such as sensors. Therefore, the local approach is coupled with other estimation algorithms such as the input independent Kalman filter to derive a robust sensor decalibration monitoring algorithm. The proposed fault detection algorithm is applied to a pilot scale process for evaluation of its performance.
In this paper, a scalar sign function-based digital design methodology is developed for modeling and control of a class of analog nonlinear systems that are restricted by the absolute value function constraints. As is found to be not uncommon, many real systems are subject to the constraints which are described by the non-smooth functions such as absolute value function. The non-smooth and nonlinear nature poses significant challenges to the modeling and control work. To overcome these difficulties, a novel idea proposed in this work is to use a scalar sign function approach to effectively transform the original nonlinear and non-smooth model into a smooth nonlinear rational function model. Upon the resulting smooth model, a systematic digital controller design procedure is established, in which an optimal linearization method, LQR design and digital implementation through an advanced digital redesign technique are sequentially applied. The example of tracking control of a piezoelectric actuator system is utilized throughout the paper for illustrating the proposed methodology.
Nonlinear, adaptive, process-model based control is demonstrated in a cascaded single-input-single-output mode for pressure drop control in a pilot-scale packed absorption column. The process is shown to be nonlinear. Control is demonstrated in both servo and regulatory modes, for no wind-up in a constrained situation, and for bumpless transfer. Model adaptation is demonstrated and shown to provide process insight. The application procedure is revealed as a design guide to aid others in implementing process-model based control.
Permanent magnet ac (PMAC) motors have existed in various configurations for many years. The advent of rare-earth magnets and their associated highly elevated levels of magnetic flux makes the permanent magnet motor attractive for many high performance applications from computer disk drives to all electric racing cars. The use of batteries as a prime storage element carries a cost penalty in terms of the unladen weight of the vehicle. Minimizing this cost function requires the minimum electric motor size and weight to be specified, while still retaining acceptable levels of output torque. This tradeoff can be achieved by applying a technique known as flux weakening which will be investigated in this paper. The technique allows the speed range of a PMAC motor to be greatly increased, giving a constant power range of more than 4:1. A dynamic model reference controller is presented which has advantages in ease of implementation, and is particularly suited to dynamic low inertia applications such as clutchless gear changing in high performance electric vehicles. The benefits of this approach are to maximize the torque speed envelope of the motor, particularly advantageous when considering low inertia operation. The controller is examined experimentally, confirming the predicted performance.
Electronic cam motion involves velocity tracking control of the master motor and trajectory generation of the slave motor. Special concerns such as the limits of the velocity, acceleration, and jerk are beyond the considerations in the conventional electronic cam motion control. This study proposes the curve-fitting of a Lagrange polynomial to the cam profile, based on trajectory optimization by cubic B-spline interpolation. The proposed algorithms may yield a higher tracking precision than the conventional master-slaves control method does, providing an optimization problem is concerned. The optimization problem contains three dynamic constraints including velocity, acceleration, and jerk of the motor system.
Previous authors have described the unstable nature of the differential equations to be solved in order to derive angular velocity components of a rigid body from an accelerometer configuration mounted on the body. Suggestions for alternatives have been made using redundant accelerometers or a combination of accelerometers and gyros. It is the purpose of this paper to present the errors in derived linear and angular kinematic variables consistent with a particular 3-2-1 accelerometer configuration for acceleration experiments conducted at the Naval Biodynamics Laboratory (NBDL). Accelerometer errors of sensitivity, linearity and orientation are considered. The statistics of those errors are obtained from repetitive calibrations of the instrumentation packages and are consistent with the calibration techniques at NBDL. Worst case combinations of the standard deviation errors in sensitivity, linearity and orientation are presented. The performance of the six-accelerometer configuration is compared with the least squares solution using three triaxial accelerometers.
This paper investigates the application of a fault diagnosis and accommodation method to a real system composed of three tanks. The performance of a closed-loop system can be altered by the occurrence of faults which can, in some circumstances, cause serious damage on the system. The research goal is to prevent the system deterioration by developing a controller that has some capabilities to compensate for faults, that is, the fault accommodation or fault-tolerant control. In this paper, a two-step scheme composed of a fault detection, isolation and estimation module, and a control compensation module is presented. The main contribution is to develop a unique structured residual generator able to isolate and estimate both sensor and actuator faults. This estimation is of paramount importance to compensate for these faults and to preserve the system performances. The application of this method to the three-tank system gives encouraging results which are presented and commented on in case of various kinds of faults.
In this paper, a new fault-tolerant control system is proposed for input-affine nonlinear plants based on Model Reference Adaptive System (MRAS) structure. The proposed method has the capability to accommodate both partial and total actuator failures along with bounded external disturbances. In this methodology, the conventional MRAS control law is modified by augmenting two compensating terms. One of these terms is added to eliminate the nonlinear dynamic, while the other is reinforced to compensate the distractive effects of the total actuator faults and external disturbances. In addition, no Fault Detection and Diagnosis (FDD) unit is needed in the proposed method. Moreover, the control structure has good robustness capability against the parameter variation. The performance of this scheme is evaluated using a CSTR system and the results were satisfactory.
This paper concerns the modelling of an accumulator used in industrial elastic web processing plant to allow changing material roll while the rest of the line remains at a constant web velocity. A nonlinear model of a motor actuated accumulator is first summarized. This model is derived from the physical relationships describing web tension and velocity dynamics in each web span of this accumulator. A linear model is deduced from the nonlinear one around a working point for frequency domain analysis. Thus the effect of some mechanical accumulator parameter variations are analyzed. In a second part, multi-model industrial PI controllers, adjusted with evolutionary algorithm on our realistic nonlinear model are compared with multi-model H∞ controllers. Both controllers allow good robustness against mechanical parameter variations.
In this paper, multichannel Kalman filters for estimation of offshore platform (OP) coordinates are designed. The complete OP motion is assumed to be composed of the low-frequency motion caused by the wind and undercurrent, and the high-frequency motion caused by the sea. The mathematical model of the low-frequency OP motion is given by the normal differential equation system, and the high-frequency OP motion is represented by a moving-average multivariable autoregression model. The parameter estimation problem for the model of the low-frequency OP motion, on which the in-service control is performed, is solved through two jointly operating Kalman filters: the first one is for the estimation of the parameters of the low-frequency motion model, and the second one is for the parameter estimation for the high-frequency model. The parameters of the first filter are automatically adapted to variations of the second filter, i.e., they are adapted to disturbances from the sea. Two algorithms for the OP motion parameter estimation (parallel and with preliminary data compression). employed for several measuring channels data estimation, are developed, and simulated on a computer. Some recommendations on their use are given.
This paper discusses the key causes of calibration drift in pressure transmitters and procedures for calibrating pressure transmitters to ensure their accuracy. Calibrating pressure transmitters involves adjusting the potentiometers in the sensor that controls the zero (lowest pressure at which a transmitter is calibrated) and span (the range of pressure the transmitter is to indicate) of the transmitter. The initial or bench calibration of pressure transmitters involves using a constant pressure source such as a deadweight tester. Once the transmitters are installed, temperature, pressure, humidity, vibration, maintenance activities, and normal aging can degrade their accuracy. Transmitter accuracy can also be degraded by transmitter sensing lines, when the water in a sensing line reference leg boils off, when non-condensable gases in the reference leg dissolve, and when voids, blockages, freezing, or leakage occur in sensing lines. On-line calibration techniques enable plants to avoid these accuracy problems by monitoring the output of an individual transmitter.
One promising attribute of the dynamic predictive modeling method introduced by Rollins et al. [D.K. Rollins, J. Liang, P. Smith, Accurate simplistic predictive modeling of nonlinear dynamic processes, ISA Transactions 37(4) (1998) 193-203] is its ability to accurately predict output response without the use of online output data. The proposed method only needs online input data to accurately predict output behavior once the semi-empirical model has been identified using offline data. This ability is critical to chemical processes because many output variables (such as chemical composition) are often measured infrequently, inaccurately, or not at all. In addition, in the presence of extremely high measurement noise of the output variable, this work will demonstrate very accurate predictive performance. Finally, this article will show that the method of Rollins et al. can predict better without the use of output data than with the use of output data in the case of large measurement variance. Thus, the proposed method is being recommended for its accuracy, especially in situations where online output response data is limited or inaccurate.
In this paper, we propose an approach for achieving detection and identification of faults, and provide fault tolerant control for systems that are modeled using timed hybrid Petri nets. For this purpose, an observer based technique is adopted which is useful in detection of faults, such as sensor faults, actuator faults, signal conditioning faults, etc. The concepts of estimation, reachability and diagnosability have been considered for analyzing faulty behaviors, and based on the detected faults, different schemes are proposed for achieving fault tolerant control using optimization techniques. These concepts are applied to a typical three tank system and numerical results are obtained.
This paper deals with the design of PI controllers which achieve the desired frequency and time domain specifications simultaneously. A systematic method, which is effective and simple to apply, is proposed. The required values of the frequency domain performance measures namely the gain and phase margins and the time domain performance measures such as settling time and overshoot are defined prior to the design. Then, to meet these desired performance values, a method which presents a graphical relation between the required performance values and the parameters of the PI controller is given. Thus, a set of PI controllers which attain desired performances can be found using the graphical relations. Illustrative examples are given to demonstrate the benefits of the method presented.
Gas-liquid two-phase flows are widely used in the chemical industry. Accurate measurements of flow parameters, such as flow regimes, are the key of operating efficiency. Due to the interface complexity of a two-phase flow, it is very difficult to monitor and distinguish flow regimes on-line and real time. In this paper we propose a cost-effective and computation-efficient acoustic emission (AE) detection system combined with artificial neural network technology to recognize four major patterns in an air-water vertical two-phase flow column. Several crucial AE parameters are explored and validated, and we found that the density of acoustic emission events and ring-down counts are two excellent indicators for the flow pattern recognition problems. Instead of the traditional Fair map, a hit-count map is developed and a multilayer Perceptron neural network is designed as a decision maker to describe an approximate transmission stage of a given two-phase flow system.
This paper describes experimental investigations of an adaptive control for suppressing thermo-acoustic instabilities in Rijke tube. Strong coupling between pressure oscillations and unsteady heat release excites a self-sustained acoustic wave which results in a loud, annoyed sound and may also lead to a structural damage to the combustion chamber. Adaptive controller based on dynamic compensation is adopted to suppress the instabilities in Rijke tube. The controller provides proper control action in response to pressure changes in combustors. Unknown noise and disturbance will be estimated and compensated actively by adaptive controller, which makes the feedback control less dependent on the precise model of the complex thermo-acoustic processes in Rijke tube. Experiment results confirm the controller employed is effective in breaking up the oscillations in Rijke tube.
This paper provides an overview of a data system upgrade to the Pratt and Whitney facility designed for making acoustic measurements on aircraft gas turbine engines. A data system upgrade was undertaken because the return-on-investment was determined to be extremely high. That is, the savings on the first test series recovered the cost of the hardware. The commercial system selected for this application utilizes 48 input channels, which allows either 1/3 octave and/or narrow-band analyses to be preformed real-time. A high-speed disk drive allows raw data from all 48 channels to be stored simultaneously while the analyses are being preformed. Results of tests to ensure compliance of the new system with regulations and with existing systems are presented. Test times were reduced from 5 h to 1 h of engine run time per engine configuration by the introduction of this new system. Conservative cost reduction estimates for future acoustic testing are 75% on items related to engine run time and 50% on items related to the overall length of the test.
Spreadsheets have become a popular computational tool and a powerful platform for performing engineering calculations. Moreover, spreadsheets include a macro language, which permits the inclusion of standard computer code in worksheets, and thereby enable developers to greatly extend spreadsheets' capabilities by designing specific add-ins. This paper describes how to use Excel spreadsheets in conjunction to Visual Basic for Application programming language to perform data acquisition and real-time control. Afterwards, the paper presents two Excel applications with interactive user interfaces developed for laboratory demonstrations and experiments in an introductory course in control.
Guarding sensors and measuring equipment is a smart operation which decouples the apparatus or systems from common mode electrical disturbances. In this context, the floating techniques are revisited and the usual measurement problem in noisy environment is outlined. It is shown that the use of differential inputs to pickup sensor continuous signals, as well as simple shielding and grounding techniques lead to increase the quality of data acquisition systems. At the other size, optical couplers allow to pass the digital version of data to an external bus or to a network by preserving the apparatus floating features.
Multivariable process control forms an important part of modern day control. While hardwired controllers still constitute the basic component of such control systems, with reducing communication latencies, controllers on the network are being mooted as a viable alternative. These controllers promise a large number of advantages in terms of reduction in wiring and greater flexibility in implementing supervisory control systems. In this paper, a study is presented which shows that UDP (User Datagram Protocol) can actually be used for real-time multivariable process control. Latency reduction algorithms used in high performance message passing systems have been used.
This paper considers the design of a software sensor (or soft-sensor) for the on-line estimation of the biological activities of a colony of aerobic micro-organisms acting on activated sludge processes, where the carbonaceous waste degradation and nitrification processes are taken into account. These bioactivities are intimately related to the dissolved oxygen concentration. Two factors that affect the dynamics of the dissolved oxygen are the respiration rate or the oxygen uptake rate (OUR) and the oxygen transfer function (K(l)a). These items are challenging topics for the application of recursive identification due the nonlinear characteristic of the oxygen transfer function, and to the time-varying feature of the respiration rate. In this work, OUR and the oxygen transfer function are estimated through a software sensor, which is based on a modified version of the discrete extended Kalman filter. Numerical simulations are carried out in a predenitrifying activated sludge process benchmark and the obtained results demonstrate the applicability and efficiency of the proposed methodology, which should provide a valuable tool to supervise and control activated sludge processes.
A two-stage robust control scheme improving the performance of an Activated Sludge Process is proposed. In the first stage, asymptotic command following the substrate concentration with simultaneous attenuation of the fluctuations of the dissolved oxygen concentration is assured. The first stage is a pure dynamic controller. The second stage is a PID controller. Good performance of the proposed control scheme on the corresponding nonlinear ASP model is illustrated through extensive simulation experiments. The contribution of the paper can be summarized to the derivation of the following two results: An accurate to a wide range of inputs and disturbances, linearized generic model of the ASP and, most important, a linear robust controller that controls accurately the effluent substrate concentration without using measurements of it.
In this paper, several tuning algorithms, specifically ITAE, IMC and Cohen and Coon, were applied in order to tune an activated sludge aeration PID controller. Performance results of these controllers were compared by simulation with those obtained by using a nonlinear fuzzy PID controller. In order to design this controller, a trial and error procedure was used to determine, as a function of error at current time and at a previous time, sets of parameters (including controller gain, integral time and derivative time) which achieve satisfactory response of a PID controller actuating over the aeration process. Once these sets of data were obtained, neural networks were used to obtain fuzzy membership functions and fuzzy rules of the fuzzy PID controller.
This paper presents the results of modeling of an inverted pendulum system driven by a linear pneumatic motor and equipped with relatively low-cost potentiometer-based position measurement system. Based on the nonlinear model of the overall pendulum system, which also includes notable friction effects, a linearized model is derived. The linearized model is used as a basis for the design of state feedback controller based on LQ and LQG optimization procedures. The linear state feedback controllers are augmented by a compensator of nonlinear friction effects whose design is based on the results of experimental identification of an appropriate static friction model. The proposed pendulum controller structures have been verified by means of computer simulations and experimentally on the experimental setup of a pneumatically actuated inverted pendulum.
There is a growing trend towards miniaturization, and with it comes an increasing need for miniature sensors and actuators for control. Moreover situations occur wherein implementation of external physical sensor is impossible, here self-sensing lends its hand appropriately. Though self-sensing actuation (SSA) is extensively studied in piezoelectric, exploring this property in shape memory alloy is still under study. A simple scheme is developed which allows differential resistance measurement of antagonistic shape memory alloy actuated wires to concurrently sense and actuate in a closed loop system. The usefulness of the proposed scheme is experimentally verified by designing a one link manipulator arm and is performed in a real time tracking control. In a practical implementation of the self-sensing actuator a newly proposed signal processing electronic circuit is used for direct differential resistance feedback control upto a bandwidth of 1.8Hz. The control design uses fuzzy PID which requires no detailed information about the constitutive model of SMA. At an operating frequency of 1Hz, the result of the self-sensing feedback control with an angular tracking accuracy of ±0.06° over a movement range of ±15° is demonstrated.
This paper presents a model of an electrohydraulic fatigue testing system that emphasizes components upstream of the servovalve and actuator. Experiments showed that there are significant supply and return pressure fluctuations at the respective ports of the servovalve. The model presented allows prediction of these fluctuations in the time domain in a modular manner. An assessment of design changes was done to improve test system bandwidth by eliminating the pressure dynamics due to the flexibility and inertia in hydraulic hoses. The model offers a simpler alternative to direct numerical solutions of the governing equations and is particularly suited for control-oriented transmission line modeling in the time domain.
This paper presents an improved indirect-driven self-sensing actuation circuit for robust vibration control of piezoelectrically-actuated flexible structures in mechatronic systems. The circuit acts as a high-pass filter and provides better self-sensing strain signals with wider sensing bandwidth and higher signal-to-noise ratio. An adaptive non-model-based control is used to compensate for the structural vibrations using the strain signals from the circuit. The proposed scheme is implemented in a PZT-actuated suspension of a commercial dual-stage hard disk drive. Experimental results show improvements of 50% and 75% in the vibration suppression at 5.4kHz and21kHz respectively, compared to the conventional PI control.
In this paper, a new framework for designing static and low order anti-windup compensator (AWC) for industrial cascade control systems with actuator saturation constraint is presented. Based on less conservative block diagonal quadratic Lyapunov function, sector boundedness, decoupled architecture, L(2) norm reduction and cascade loop compensation, linear matrix inequalities are developed which guarantee stability and suitable performance for overall closed-loop system. Static AWC parameters are obtained by comparing the full order AWC architecture with generalized architecture for cascade control system. Low order AWC is designed by sub-optimal approach in which AWC weights are tuned by designer. Anti-windup compensator is divided into inner and outer loop compensators which compensate the effect of saturation at each level. It is observed that the proposed methodology is less conservative than the traditional AWC schemes when applied to cascade control systems. The proposed scheme is successfully tested experimentally on a temperature-based process control system and results are outlined.
This paper presents a new intelligent approach for adaptive control of a nonlinear dynamic system. A modified version of the brain emotional learning based intelligent controller (BELBIC), a bio-inspired algorithm based upon a computational model of emotional learning which occurs in the amygdala, is utilized for position controlling a real laboratorial rotary electro-hydraulic servo (EHS) system. EHS systems are known to be nonlinear and non-smooth due to many factors such as leakage, friction, hysteresis, null shift, saturation, dead zone, and especially fluid flow expression through the servo valve. The large value of these factors can easily influence the control performance in the presence of a poor design. In this paper, a mathematical model of the EHS system is derived, and then the parameters of the model are identified using the recursive least squares method. In the next step, a BELBIC is designed based on this dynamic model and utilized to control the real laboratorial EHS system. To prove the effectiveness of the modified BELBIC's online learning ability in reducing the overall tracking error, results have been compared to those obtained from an optimal PID controller, an auto-tuned fuzzy PI controller (ATFPIC), and a neural network predictive controller (NNPC) under similar circumstances. The results demonstrate not only excellent improvement in control action, but also less energy consumption.
In this work we show that the anti-wind-up-bumpless-transfer controller emerges from the structure of model predictive control (MPC) with quadratic objective and input constrains. The key to establish that relationship is the application of optimality conditions to the equivalent optimal control problem. The proposed framework employs a model of physical constraints as part of the controller architecture to ensure that the commands sent to the actuator do not exceed their specific limits and the internal states of the controller are well updated. Numerical examples are presented for illustrating the proposed control design methodology.