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Selected AbstractsKalman filter-based adaptive control for networked systems with unknown parameters and randomly missing outputsINTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL, Issue 18 2009Y. Shi Abstract This paper investigates the problem of adaptive control for networked control systems with unknown model parameters and randomly missing outputs. In particular, for a system with the autoregressive model with exogenous input placed in a network environment, the randomly missing output feature is modeled as a Bernoulli process. Then, an output estimator is designed to online estimate the missing output measurements, and further a Kalman filter-based method is proposed for parameter estimation. Based on the estimated output and the available output, and the estimated model parameters, an adaptive control is designed to make the output track the desired signal. Convergence properties of the proposed algorithms are analyzed in detail. Simulation examples illustrate the effectiveness of the proposed method. Copyright © 2008 John Wiley & Sons, Ltd. [source] Controller design for natural and robotic systems with transmission delaysJOURNAL OF FIELD ROBOTICS (FORMERLY JOURNAL OF ROBOTIC SYSTEMS), Issue 5 2002Abhay Kataria Robust stability and two-dimensional trajectory following problems are considered for n -link robotic systems with transmission delays. Such problems appear in telerobotics, where the controller is physically far from the robot, and in neural control of musculo-skeletal (biological) systems, where muscle actuation and neural sensing are subject to time delays. A typical second-order nonlinear dynamical model is taken with input and output time delays. In a prior work by the authors, a control strategy was developed for stable movement of the planar linkage system, using the standard Q -parameterization and solving an H, control problem to determine the free parameter. In this article, a new control scheme is proposed to eliminate the steady-state errors seen in the tracking performance of the controller derived in the earlier work. Simulation examples are shown to demonstrate the effectiveness of the proposed control methodology. © 2002 Wiley Periodicals, Inc. [source] State-feedback adaptive tracking of linear systems with input and state delaysINTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING, Issue 6 2009Boris Mirkin Abstract A state-feedback Lyapunov-based design of direct model reference adaptive control is developed for a class of linear systems with input and state delays based only on lumped delays without so-called distributed-delay blocks. The design procedure is based on the concept of reference trajectory prediction, and on the formulation of an augmented error. We propose a controller parametrization that attempts to anticipate the future states. An appropriate Lyapunov,Krasovskii type functional is found for the design and the stability analysis. A simulation example illustrates the new controller. Copyright © 2008 John Wiley & Sons, Ltd. [source] Adaptive regulation of MIMO linear systems against unknown sinusoidal exogenous inputsINTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING, Issue 6 2009Maurizio Ficocelli Abstract This paper deals with the adaptive regulation problem in linear multi-input multi-output systems subject to unknown sinusoidal exogenous inputs, where the frequencies, amplitudes, and phases of the sinusoids are unknown and where the number of sinusoids is assumed to be known. The design of an adaptive regulator for the system under consideration is performed within a set of Q -parameterized stabilizing controllers. To facilitate the design of the adaptive regulator, triangular decoupling is introduced in part of the closed-loop system dynamics. This is achieved through the proper selection of the controller state feedback gain and the structure of the Q parameter. Regulation conditions are then presented for the case where the sinusoidal exogenous input properties are known. For the case where the sinusoidal exogenous input properties are unknown, an adaptation algorithm is proposed to tune the Q parameter in the expression of the parameterized controller. The online tuning of the Q parameter allows the controller to converge to the desired regulator. Convergence results of the adaptation algorithm are presented. A simulation example involving a retinal imaging adaptive optics system is used to illustrate the performance of the proposed adaptive system. Copyright © 2008 John Wiley & Sons, Ltd. [source] Simultaneous input and parameter estimation with input observers and set-membership parameter bounding: theory and an automotive applicationINTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING, Issue 5 2006I. Kolmanovsky Abstract The paper addresses an on-line, simultaneous input and parameter estimation problem for a first-order system affected by measurement noise. This problem is motivated by practical applications in the area of engine control. Our approach combines an input observer for the unknown input with a set-membership algorithm to estimate the parameter. The set-membership algorithm takes advantage of a priori available information such as (i) known bounds on the unknown input, measurement noise and time rate of change of the unknown input; (ii) the form of the input observer in which the unknown parameter affects only the observer output; and (iii) the input observer error bounds for the case when the parameter is known exactly. The asymptotic properties of the algorithm as the observer gain increases are delineated. It is shown that for accurate estimation the unknown input needs to approach the known bounds a sufficient number of times (these time instants need not be known). Powertrain control applications are discussed and a simulation example based on application to engine control is reported. A generalization of the basic ideas to higher order systems is also elaborated. Copyright © 2006 John Wiley & Sons, Ltd. [source] Exponential convergence of the Kalman filter based parameter estimation algorithmINTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING, Issue 10 2003Liyu Cao Abstract In this paper we shall present a new method to analyse the convergence property of the Kalman filter based parameter estimation algorithms. This method for convergence analysis is mainly based on some matrix inequalities and is more simple than some of the existing approaches in the literature. This method can simultaneously provide both lower and upper bounds on the exponential convergence rate as the functions of bounds of the related matrices, such as the covariance matrices. A simulation example is provided to illustrate the convergence property of the Kalman filter based algorithms. Copyright © 2003 John Wiley & Sons, Ltd. [source] Anti-windup synthesis for nonlinear dynamic inversion control schemesINTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL, Issue 13 2010G. Herrmann Abstract A general anti-windup (AW) compensation scheme is provided for a class of input constrained feedback-linearizable nonlinear systems. The controller considered is an inner-loop nonlinear dynamic inversion controller, augmented with an outer-loop linear controller, of arbitrary structure. For open-loop globally exponentially stable plants, it is shown that (i) there always exists a globally stabilizing AW compensator corresponding to a nonlinear generalization of the Internal-Model-Control (IMC) AW solution; (ii) important operator theoretic parallels exist between the AW design scheme for linear control and the suggested AW design scheme for nonlinear affine plants and (iii) a more attractive AW compensator may be obtained by using a nonlinear state-feedback term, which plays a role similar to the linear state-feedback term in linear coprime factor-based AW compensation. The results are demonstrated on a dual-tank simulation example. Copyright © 2009 John Wiley & Sons, Ltd. [source] H, fuzzy control design of discrete-time nonlinear active fault-tolerant control systemsINTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL, Issue 10 2009Huai-Ning Wu Abstract This paper is concerned with the problem of H, fuzzy controller synthesis for a class of discrete-time nonlinear active fault-tolerant control systems (AFTCSs) in a stochastic setting. The Takagi and Sugeno (T,S) fuzzy model is employed to exactly represent a nonlinear AFTCS. For this AFTCS, two random processes with Markovian transition characteristics are introduced to model the failure process of system components and the fault detection and isolation (FDI) decision process used to reconfigure the control law, respectively. The random behavior of the FDI process is conditioned on the state of the failure process. A non-parallel distributed compensation (non-PDC) scheme is adopted for the design of the fault-tolerant control laws. The resulting closed-loop fuzzy system is the one with two Markovian jump parameters. Based on a stochastic fuzzy Lyapunov function (FLF), sufficient conditions for the stochastic stability and H, disturbance attenuation of the closed-loop fuzzy system are first derived. A linear matrix inequality (LMI) approach to the fuzzy control design is then developed. Moreover, a suboptimal fault-tolerant H, fuzzy controller is given in the sense of minimizing the level of disturbance attenuation. Finally, a simulation example is presented to illustrate the effectiveness of the proposed design method. Copyright © 2008 John Wiley & Sons, Ltd. [source] Global stabilization of uncertain stochastic nonlinear time-delay systems by output feedbackINTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL, Issue 9 2008Peng Cui Abstract Constructive control techniques have been proposed for controlling strict feedback (lower triangular form) stochastic nonlinear systems with a time-varying time delay in the state. The uncertain nonlinearities are assumed to be bounded by polynomial functions of the outputs multiplied by unmeasured states or delayed states. The delay-independent output feedback controller making the closed-loop system globally asymptotically stable is explicitly constructed by using a linear dynamic high-gain observer in combination with a linear dynamic high-gain controller. A simulation example is given to demonstrate the effectiveness of the proposed design procedure. Copyright © 2007 John Wiley & Sons, Ltd. [source] Predictor-based repetitive learning control for a class of remote control nonlinear systemsINTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL, Issue 16 2007Ya-Jun Pan Abstract In this paper, a repetitive learning control (RLC) approach is proposed for a class of remote control nonlinear systems satisfying the global Lipschitz condition. The proposed approach is to deal with the remote tracking control problem when the environment is periodic or repeatable over infinite time domain. Since there exist time delays in the two transmission channels: from the controller to the actuator and from the sensor to the controller, tracking a desired trajectory through a remote controller is not an easy task. In order to solve the problem caused by time delays, a predictor is designed on the controller side to predict the future state of the nonlinear system based on the delayed measurements from the sensor. The convergence of the estimation error of the predictor is ensured. The gain design of the predictor applies linear matrix inequality (LMI) techniques developed by Lyapunov Kravoskii method for time delay systems. The RLC law is constructed based on the feedback error from the predicted state. The overall tracking error tends to zero asymptotically over iterations. The proof of the stability is based on a constructed Lyapunov function related to the Lyapunov Kravoskii functional used for the proof of the predictor's convergence. By well incorporating the predictor and the RLC controller, the system state tracks the desired trajectory independent of the influence of time delays. A numerical simulation example is shown to verify the effectiveness of the proposed approach. Copyright © 2007 John Wiley & Sons, Ltd. [source] New results in robust actuator fault reconstruction for linear uncertain systems using sliding mode observersINTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL, Issue 14 2007Kok Yew Ng Abstract This paper presents a robust actuator fault reconstruction scheme for linear uncertain systems using sliding mode observers. In existing work, fault reconstruction via sliding mode observers is limited to either linear certain systems subject to unknown inputs, relative degree one systems or a specific class of relative degree two systems. This paper presents a new method that is applicable to a wider class of systems with relative degree higher than one, and can also be used for systems with more unknown inputs than outputs. The method uses two sliding mode observers in cascade. Signals from the first observer are processed and used to drive the second observer. Overall, this results in actuator fault reconstruction being feasible for a wider class of systems than using existing methods. A simulation example verifies the claims made in this paper. Copyright © 2007 John Wiley & Sons, Ltd. [source] Robust inverse optimal control laws for nonlinear systemsINTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL, Issue 15 2003Nael H. El-Farra Abstract This work proposes a robust inverse optimal controller design for a class of nonlinear systems with bounded, time-varying uncertain variables. The basic idea is that of re-shaping the scalar nonlinear gain of an LgV controller, based on Sontag's formula, so as to guarantee certain uncertainty attenuation properties in the closed-loop system. The proposed gain re-shaping is shown to yield a control law that enforces global boundedness of the closed-loop trajectories, robust asymptotic output tracking with an arbitrary degree of attenuation of the effect of uncertainty on the output, and inverse optimality with respect to a meaningful cost that penalizes the tracking error and the control action. The performance of the control law is illustrated through a simulation example and compared with other controller designs. Copyright © 2003 John Wiley & Sons, Ltd. [source] Robust adaptive fuzzy controller for non-affine nonlinear systems with dynamic rule activationINTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL, Issue 2 2003Jang-Hyun Park Abstract This paper describes the design of a robust adaptive fuzzy controller for an uncertain single-input single-output nonlinear dynamical systems. While most recent results on fuzzy controllers considers affine systems with fixed rule-base fuzzy systems, we propose a control scheme for non-affine nonlinear systems and a dynamic fuzzy rule activation scheme in which an appropriate number of the fuzzy rules are chosen on-line. By using the proposed scheme, we can reduce the computation time, storage space, and dynamic order of the adaptive fuzzy system without significant performance degradation. The Lyapunov synthesis approach is used to guarantee a uniform ultimate boundedness property for the tracking error, as well as for all other signals in the closed loop. No a priori knowledge of an upper bounds on the uncertainties is required. The theoretical results are illustrated through a simulation example. Copyright © 2002 John Wiley & Sons, Ltd. [source] Composition cascade control for chemical reactorsINTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL, Issue 13 2002Jose Alvarez-Ramirez Abstract Eventhough the composition control of chemical reactors is an old, widely studied, and still relevant problem in chemical process control, it still presents some aspects that remain unexplored or unresolved. For instance, a unifying approach is needed to systematize the existing ad hoc controller constructions, to rigorously explain their remarkable robustness property, and to explore the possibility of improving their construction and functioning. In this paper, some aspects of these control problems are addressed by resorting to recently developed approaches in constructive non-linear control, yielding a systematic controller construction coupled to a simple tuning scheme that can be executed with standard tuning rules, a closed-loop stability criterion, and an explanation of the closed-loop dynamics behaviour. Specifically, a linear cascade (master/slave) control configuration is proposed, which leads to global internal stability of the controlled system with asymptotic regulation of the output-stream composition about a given desired setpoint. A simulation example is used to illustrate the results. Copyright © 2002 John Wiley & Sons, Ltd. [source] An efficient nonlinear programming strategy for PCA models with incomplete data setsJOURNAL OF CHEMOMETRICS, Issue 6 2010Rodrigo López-Negrete de la Fuente Abstract Processing plants can produce large amounts of data that process engineers use for analysis, monitoring, or control. Principal component analysis (PCA) is well suited to analyze large amounts of (possibly) correlated data, and for reducing the dimensionality of the variable space. Failing online sensors, lost historical data, or missing experiments can lead to data sets that have missing values where the current methods for obtaining the PCA model parameters may give questionable results due to the properties of the estimated parameters. This paper proposes a method based on nonlinear programming (NLP) techniques to obtain the parameters of PCA models in the presence of incomplete data sets. We show the relationship that exists between the nonlinear iterative partial least squares (NIPALS) algorithm and the optimality conditions of the squared residuals minimization problem, and how this leads to the modified NIPALS used for the missing value problem. Moreover, we compare the current NIPALS-based methods with the proposed NLP with a simulation example and an industrial case study, and show how the latter is better suited when there are large amounts of missing values. The solutions obtained with the NLP and the iterative algorithm (IA) are very similar. However when using the NLP-based method, the loadings and scores are guaranteed to be orthogonal, and the scores will have zero mean. The latter is emphasized in the industrial case study. Also, with the industrial data used here we are able to show that the models obtained with the NLP were easier to interpret. Moreover, when using the NLP many fewer iterations were required to obtain them. Copyright © 2010 John Wiley & Sons, Ltd. [source] Manipulating deformable linear objects: Attachable adjustment-motions for vibration reductionJOURNAL OF FIELD ROBOTICS (FORMERLY JOURNAL OF ROBOTIC SYSTEMS), Issue 7 2001Shigang Yue This paper addresses the problem of handling deformable linear objects in a suitable way to avoid acute vibration. Different types of adjustment-motions that eliminate vibration of deformable objects and that can be attached to the end of an arbitrary end-effector's trajectory are presented. For describing the dynamics of deformable linear objects, the finite element method is used to derive the dynamic differential equations. A genetic algorithm is used to find the optimal adjustment motion for each simulation example. Experiments are conducted to verify the presented manipulating method. © 2001 John Wiley & Sons, Inc. [source] Model-based synthesis of nonlinear PI and PID controllersAICHE JOURNAL, Issue 8 2001Raymond A. Wright PI and PID controllers continue to be popular methods in industrial applications. It is well known that linear PI and PID controllers result from the application of model-based controller design methods to linear first- and second-order systems. It is shown that nonlinear PI and PID controllers result from the application of nonlinear controller design methods to nonlinear first- and second-order systems. As a result, the controllers resulting from nonlinear model-based control theory are put in a convenient form, more amenable to industrial implementation. Additionally, the quantities used in the controller are useful for monitoring the process and quantifying modeling error. Chemical engineering examples are used to illustrate the resulting control laws. A simulation example further demonstrates the performance of the nonlinear controllers, as well as their useful process monitoring quantities. [source] Product transfer between plants using historical process dataAICHE JOURNAL, Issue 10 2000Christiane M. Jaeckle Based on the concepts laid out in an earlier article (Jaeckle and MacGregor, 1998), this paper defines the problem of moving the production of a particular product grade from a plant A to another plant B when both plants have already produced a similar range of grades. Since the two plants may differ in size, configurations, and so on, the process conditions required to produce any given product grade may be very different in the two plants. How historical process data on both plants may be utilized to assist in this problem is investigated. A multivariate latent variable method is proposed that uses data from both plants to predict process conditions for plant B for a grade previously produced only in plant A. The approach is illustrated by a simulation example. [source] Robust sliding mode design for uncertain stochastic systems based on H, control methodOPTIMAL CONTROL APPLICATIONS AND METHODS, Issue 2 2010Yugang Niu Abstract In this paper, the design problem of sliding mode control (SMC) is addressed for uncertain stochastic systems modeled by Itô differential equations. There exist the parameter uncertainties in both the state and input matrices, as well as the unmatched external disturbance. The key feature of this work is the integration of SMC method with H, technique such that the robust stochastic stability with a prescribed disturbance attenuation level , can be achieved. A sufficient condition for the existence of the desired sliding mode controller is obtained via linear matrix inequalities. The reachability of the specified sliding surface is proven. Finally, a numerical simulation example is presented to illustrate the proposed method. Copyright © 2009 John Wiley & Sons, Ltd. [source] Properties of parameter-dependent open-loop MPC for uncertain systems with polytopic description,ASIAN JOURNAL OF CONTROL, Issue 1 2010Baocang Ding Abstract This paper investigates the parameter-dependent open-loop model predictive control (PDOLMPC) scheme for systems with a polytopic uncertainty description. PDOLMPC parameterizes the infinite horizon control moves into a number of free control moves followed by a single state feedback law. The free control moves (excluding the first one) are parameter dependent and constructed upon all of the extreme realizations of the uncertainty before the switching horizon N. Our primary contribution is to point out that this PDOLMPC is a relaxed version of the feedback MPC. Thus, some properties of nominal MPC, such as enhancement of optimality and enlargement of region of attraction by increasing the switching horizon, can be inherited in PDOLMPC. These properties are theoretically important for robust MPC and a simulation example is given for demonstration. Copyright © 2009 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society [source] Poly-quadratic stability of discrete-time nonlinear systems in Takagi-Sugeno's form,ASIAN JOURNAL OF CONTROL, Issue 6 2009Baocang Ding Abstract This paper studies poly-quadratic stability of nonlinear systems represented by a Takagi-Sugeno (T-S) discrete fuzzy model. A system is poly-quadratically stable when its stability can be verified by a parameter dependent Lyapunov function. There are already some results in this area. This paper, however, presents less conservative results by adopting more slack-matrix-variables in the linear matrix inequalities (LMIs). The parallel distributed compensation (PDC) law is utilized in both the analysis and the synthesis problems. The effectiveness of the new results in this paper is validated by a simulation example. Copyright © 2009 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society [source] Adaptive output feedback control for a class of planar nonlinear systems,ASIAN JOURNAL OF CONTROL, Issue 5 2009Fang Shang Abstract This paper is concerned with the problem of global adaptive stabilization by output feedback for a class of planar nonlinear systems with uncertain control coefficient and unknown growth rate. The control coefficient is not supposed to have known upper bound, and this relaxes the corresponding requirement in the existing literature (see e.g. 1, 2. First, by the universal control method, an observer is constructed based on the dynamic high-gain K-filters. Then, the control design procedure is developed to obtain the stabilizing controller and dynamic compensator for the uncertainties in the control coefficient. It is shown that the global stability of the closed-loop system can be guaranteed by the appropriate choice of the design parameters. A simulation example is also provided to illustrate the correctness of the theoretical results. © 2009 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society. [source] DISTURBANCE REJECTION USING AN ILC ALGORITHM WITH ITERATION VARYING FILTERSASIAN JOURNAL OF CONTROL, Issue 3 2004M. Norrlöf ABSTRACT An Iterative Learning Control disturbance rejection approach is considered and it is shown that iteration variant learning filters can asymptotically give the controlled variable zero error and zero variance. Convergence is achieved with the assumption that the relative model error is less than one. The transient response of the suggested ILC algorithm is also discussed using a simulation example. [source] A Design Of Multiloop Predictive Self-Tuning Pid ControllersASIAN JOURNAL OF CONTROL, Issue 4 2002Masaru Katayama ABSTRACT In this paper, a new design scheme of multiloop predictive self-tuning PID controllers is proposed for multivariable systems. The proposed scheme firstly uses a static pre-compensator as an approximately decoupling device, in order to roughly reduced the interaction terms of the controlled object. The static matrix pre-compensator is adjusted by an on-line estimator. Furthermore, by regarding the approximately decoupled system as a series of single-input single-output subsystems, a single-input single-output PID controller is designed for each subsystem. The PID parameters are calculated on-line based on the relationship between the PID control and the generalized predictive control laws. The proposed scheme is numerically evaluated on a simulation example. [source] MOMENT ESTIMATION IN THE CLASS OF BISEXUAL BRANCHING PROCESSES WITH POPULATION,SIZE DEPENDENT MATINGAUSTRALIAN & NEW ZEALAND JOURNAL OF STATISTICS, Issue 1 2007Miguel González Summary This paper concerns the estimation of the offspring mean vector, the covariance matrix and the growth rate in the class of bisexual branching processes with population-size dependent mating. For the proposed estimators, some unconditional moments and some conditioned to non-extinction are determined and asymptotic properties are established. Confidence intervals are obtained and, as illustration, a simulation example is given. [source] Flow-induced vibrations of non-linear cables.INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN ENGINEERING, Issue 5 2002Part 1: Models, algorithms Abstract In this paper, we develop governing equations for non-linear cables as well as a formulation for the coupled flow-structure problem. The structure is discretized with second-order accuracy while the flow is discretized using spectral/hp elements in the context of the arbitrary Lagrangian,Eulerian formulation (ALE). Several benchmark problems are considered and the computational implementation is detailed. In the second part of this work large-scale simulation examples are presented. Copyright © 2002 John Wiley & Sons, Ltd. [source] Robust adaptive output-feedback control for a class of nonlinear systems with time-varying actuator faultsINTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING, Issue 9 2010Zhengqiang Zhang Abstract A robust adaptive output-feedback control scheme is proposed for a class of nonlinear systems with unknown time-varying actuator faults. Additional unmodelled terms in the actuator fault model are considered. A new linearly parameterized model is proposed. The boundedness of all the closed-loop signals is established. The desired control performance of the closed-loop system is guaranteed by appropriately choosing the design parameters. The properties of the proposed control algorithm are demonstrated by two simulation examples. Copyright © 2010 John Wiley & Sons, Ltd. [source] Adaptive tracking control for electrically-driven robots without overparametrizationINTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING, Issue 2 2002Yeong-Chan Chang Abstract This paper addresses the motion tracking control of robot systems actuated by brushed direct current motors in the presence of parametric uncertainties and external disturbances. By using the integrator backstepping technique, two kinds of adaptive control schemes are developed: one requires the measurements of link position, link velocity and armature current for feedback and the other requires only the measurements of link position and armature current for feedback. The developed adaptive controllers guarantee that the resulting closed-loop system is locally stable, all the states and signals are bounded, and the tracking error can be made as small as possible. The attraction region can be not only arbitrarily preassigned but also explicitly constructed. The main novelty of the developed adaptive control laws is that the number of parameter estimates is exactly equal to the number of unknown parameters throughout the entire electromechanical system. Consequently, the phenomenon of overparametrization, a significant drawback of employing the integrator backstepping technique to treat the control of electrically driven robots in the previous literature, is eliminated in this study. Finally, simulation examples are given to illustrate the tracking performance of electrically driven robot manipulators with the developed adaptive control schemes. Copyright © 2002 John Wiley & Sons, Ltd. [source] Speed-up and performance evaluation of piecewise-linear DC analysisINTERNATIONAL JOURNAL OF CIRCUIT THEORY AND APPLICATIONS, Issue 4 2007Janne RoosArticle first published online: 29 NOV 200 Abstract The good convergence properties of piecewise-linear (PWL) DC analysis have been thoroughly discussed in many papers. This paper, in turn, concentrates on the speed of PWL DC analysis, where the boundary crossing of linear regions plays a crucial role. Fast methods are presented for performing the following boundary-crossing computations: LU-decomposition update, matrix-equation solution, boundary-crossing direction, and damping-factor determination. Special attention is given to those PWL DC analysis methods that perform PWL modelling of the non-linear components on the fly; an adaptive method is proposed for controlling the accuracy of PWL modelling and speeding up simulation. The computational efficiency of the accelerated PWL DC analysis is discussed and compared with that of conventional, Newton,Raphson iteration-based, DC analysis. Finally, the performance evaluation is completed with realistic simulation examples: it is demonstrated that the speed of the accelerated PWL DC analysis is comparable with that of the conventional DC analysis. Copyright © 2006 John Wiley & Sons, Ltd. [source] Microwave imaging of parallel perfectly conducting cylindersINTERNATIONAL JOURNAL OF IMAGING SYSTEMS AND TECHNOLOGY, Issue 6 2000Anyong Qing This paper considers microwave imaging of parallel perfectly conducting cylinders using a solution of the scattering problem by the point-matching method. A cubic B-spline, real-coded genetic algorithm and an adaptive hybrid algorithm are proposed to solve the inverse problem. Previous shape functions in trigonometric series with arbitrary coefficients are nondefinite, which intensify the ill-posedness and slow the early time convergence of the algorithm. A novel shape function based on cubic B-splines is developed and the real-coded genetic algorithm is modified accordingly. Numerical simulation examples show that the early time convergence of the real-coded genetic algorithm is improved significantly. Next, the adaptive hybrid algorithm is developed to improve the late time convergence of the cubic B-spline real-coded genetic algorithm. © 2001 John Wiley & Sons, Inc. Int J Imaging Syst Technol 11, 365,371, 2000 [source] | ||||||||||||||||||||||||||||