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Journal ArticleDOI

Adaptive Fuzzy-Wavelet Neural Network identification core for reinforced control of general arbitrarily switched nonlinear Multi Input-Multi Output Dynamic Systems

01 Jun 2020-Applied Soft Computing (Elsevier)-Vol. 91, pp 106265
TL;DR: This study proposes that the aforementioned problems can be overcome by designing a control scheme that prioritizes appropriate objectives according to operating conditions, and proposes a dual-mode scheme that ensures robust stabilization in safe control modes corresponding to transient-state stage and accurate tracking in steady- state stage of system response based on the proposed precise mode scheme.
About: This article is published in Applied Soft Computing.The article was published on 2020-06-01. It has received 18 citations till now. The article focuses on the topics: Sliding mode control & Robustness (computer science).
Citations
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Journal ArticleDOI
TL;DR: A novel unknown input observer (UIO)-integrated extended finite impulse response (EFIR) estimator and its application for an effective sensor fault-tolerant control (FTC) of an electrohydraulic actuator (EHA) is presented.
Abstract: This article presents a novel unknown input observer (UIO)-integrated extended finite impulse response (EFIR) estimator and its application for an effective sensor fault-tolerant control (FTC) of an electrohydraulic actuator (EHA). The proposed estimator exploits the UIO structure in the EFIR filter. Thus, it requires only a small amount of historical data ( $N$ ) while ensuring the following: 1) sensor fault and system state estimation accuracy under time-correlated noise; 2) the number of estimator design parameters is significantly minimized; and 3) robust residual generation. A Lyapunov-stability-based theory is carried out to study its convergence condition. Next, an EHA-based test rig has been set up, and sensor FTC is performed by carrying this estimator as part of a fault diagnosis algorithm to evaluate its performance by both simulation and real-time experiments. Results highlight that under optimal setting ( $N=N_{\rm opt}$ ), the estimator performance is near accurate to the very well developed extended-Kalman-filter-based UIO in undisturbed conditions but significantly outperforms when dealing with time-correlated noise under the same control environment. The estimator also shows its robustness under below-optimal setting (downgrading $N_{\rm opt}$ by 50%) while performing sensor FTC in real time.

14 citations

Journal ArticleDOI
TL;DR: It is proposed that control objectives and stability conditions can be relaxed such that boundedness of sliding functions in all switched modes is maintained according to the cost-reducing input update law rather than their strict convergence to the origin.

10 citations

Journal ArticleDOI
TL;DR: A Discrete-Time Sliding Mode Control (DTSMC)-based tracking control algorithm named as Position-Braking Tracking Control (PBTC) is introduced in which the servo PMDC is controlled in position tracking mode when motoring/reverse motoring property is expected.

9 citations

Journal ArticleDOI
TL;DR: In this article , a fuzzy deep wavelet neural network (FDWNN) inversion method was proposed for electrical resistivity imaging (ERI) in which an adaptive shuffled frog leaping algorithm (ASFLA) was introduced to balance exploration and exploitation during the search process.
Abstract: Electrical resistivity imaging (ERI) is a non-invasive imaging technique for measuring resistivity, and the inversion problem of ERI is non-linear and non-convex. Traditional fuzzy neural network based on gradient descent is known to be inept for its low accuracy and does not ensure global convergence. In order to solve above problems, we present a fuzzy deep wavelet neural network (FDWNN) inversion method trained by an accelerated hybrid learning algorithm to invert resistivity data of ERI. Firstly, a novel FDWNN model, which integrates the fuzzy clustering-based premise part with the deep WNN-based consequent part, is applied to improve the prediction accuracy and enhance the interpretability of ERI inversion. Secondly, an adaptive shuffled frog leaping algorithm (ASFLA) is introduced to balance the exploration and exploitation during the search process intelligently. In the proposed ASFLA, an adaptive mutation rule is applied to improve the local search and a differential leaping strategy is presented to enhance the global search. Finally, an accelerated hybrid learning algorithm integrating the ASFLA and a weight decay backpropagation (wdBP) method is designed, which keeps the advantages of the SFLA in finding global optimal values, while speeds up the convergence and improves the generalization through wdBP simultaneously. Moreover, five experiments are introduced to evaluate the feasibility and applicability of the FDWNN algorithm by comparison with other contenders.

7 citations

Journal ArticleDOI
TL;DR: In this article , a constrained nonlinear parameter selection problem (CNPSP) is formulated as a constrained optimization problem and a penalty function-based random search (PFRS) algorithm is designed for solving the CNPSP based on a search rule-based penalty function (NSRPF) method and a novel random search algorithm.

7 citations

References
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Book
24 Jun 2003
TL;DR: I. Stability under Arbitrary Switching, Systems not Stabilizable by Continuous Feedback, and Systems with Sensor or Actuator Constraints with Large Modeling Uncertainty.
Abstract: I. INTRODUCTION 1. Basic Concepts II . STABILITY OF SWITCHED SYSTEMS 2. Stability under Arbitrary Switching 3. Stability under Constrained Switching III. SWITCHING CONTROL 4. Systems not Stabilizable by Continuous Feedback 5. Systems with Sensor or Actuator Constraints 6. Systems with Large Modeling Uncertainty IV. SUPPLEMENTARY MATERIAL A. Stability B. Lie Algebras Notes and References Bibliography Index

5,844 citations

Book
01 Jan 1987
TL;DR: In this paper, the authors describe the historical development of the classical theory of linear methods for solving nonstiff ODEs and present a modern treatment of Runge-Kutta and extrapolation methods.
Abstract: This book deals with methods for solving nonstiff ordinary differential equations. The first chapter describes the historical development of the classical theory, and the second chapter includes a modern treatment of Runge-Kutta and extrapolation methods. Chapter three begins with the classical theory of multistep methods, and concludes with the theory of general linear methods. The reader will benefit from many illustrations, a historical and didactic approach, and computer programs which help him/her learn to solve all kinds of ordinary differential equations. This new edition has been rewritten and new material has been included.

3,307 citations

Journal ArticleDOI
TL;DR: The main idea is to design a Lyapunov-based predictive controller for each constituent mode in which the switched system operates and incorporate constraints in the predictive controller design which upon satisfaction ensure that the prescribed transitions between the modes occur in a way that guarantees stability of the switched closed-loop system.
Abstract: In this work, a predictive control framework is proposed for the constrained stabilization of switched nonlinear systems that transit between their constituent modes at prescribed switching times. The main idea is to design a Lyapunov-based predictive controller for each constituent mode in which the switched system operates and incorporate constraints in the predictive controller design which upon satisfaction ensure that the prescribed transitions between the modes occur in a way that guarantees stability of the switched closed-loop system. This is achieved as follows: For each constituent mode, a Lyapunov-based model predictive controller (MPC) is designed, and an analytic bounded controller, using the same Lyapunov function, is used to explicitly characterize a set of initial conditions for which the MPC, irrespective of the controller parameters, is guaranteed to be feasible, and hence stabilizing. Then, constraints are incorporated in the MPC design which, upon satisfaction, ensure that: 1) the state of the closed-loop system, at the time of the transition, resides in the stability region of the mode that the system is switched into, and 2) the Lyapunov function for each mode is nonincreasing wherever the mode is reactivated, thereby guaranteeing stability. The proposed control method is demonstrated through application to a chemical process example.

358 citations

Journal ArticleDOI
TL;DR: Inspired by the theory of multiresolution analysis (MRA) of wavelet transforms and fuzzy concepts, a fuzzy wavelet network (FWN) is proposed for approximating arbitrary nonlinear functions.
Abstract: Inspired by the theory of multiresolution analysis (MRA) of wavelet transforms and fuzzy concepts, a fuzzy wavelet network (FWN) is proposed for approximating arbitrary nonlinear functions. The FWN consists of a set of fuzzy rules. Each rule corresponding to a sub-wavelet neural network (WNN) consists of single-scaling wavelets. Through efficient bases selection, the dimension of the approximated function does not cause the bottleneck for constructing FWN. Especially, by learning the translation parameters of the wavelets and adjusting the shape of membership functions, the model accuracy and the generalization capability of the FWN can be remarkably improved. Furthermore, an algorithm for constructing and training the fuzzy wavelet networks is proposed. Simulation examples are also given to illustrate the effectiveness of the method.

290 citations

Journal ArticleDOI
TL;DR: It is shown that the newly proposed non-smooth control-based DSMC can guarantee the same level of accuracy for the sliding mode motion as that of an equivalent control- based DSMC.

250 citations