Fuzzy adaptive control of a class of nonlinear systems with. In 10, a robust adaptive fuzzy tracking controller was designed for purefeedback stochastic nonlinear systems with input constraints. On the other hand, 11 deal with the problem of adaptive fuzzy control for nonstrictfeedback systems with input saturation and output constraint. Sep, 2017 in this paper, a stability analysis is suggested for adaptive fuzzy logic systems flss without the requirement of states measurement or estimation. The above observations motivate the present research, in which we investigate adaptive fuzzy control for nonlinear systems with timevarying delays. Pdf adaptive fuzzy systems and control design and stability. The theoretic basis and a design procedure are proposed and their validity is demonstrated through application experiments for the precise regulation control of enteral feeding pump. This new adaptive controller uses a fuzzy multilayered architecture. Observerbased robust adaptive fuzzy control for uncertain. Adaptive fuzzy control for fractionalorder interconnected systems with unknown control directions bingyun liang, shiqi zheng, choon ki ahn, senior member, ieee, and feng liu abstract this paper concentrates on the study of the decentralized fuzzy control method for a class of fractionalorder interconnected systems with unknown control directions.
Adaptive fuzzy slidingmode control based on generalized t. Stability analysis in pdf format, in that case you come on to. Direct adaptive fuzzy control for nonlinear systems with time. Research article adaptive fuzzy sliding mode tracking. It summarizes the stateoftheart methods for automatic tuning of the parameters and structures of fuzzy logic systems, and shows both the details of how to apply them to a variety of control and signal processing problems, and how. If you are searched for the ebook by lixin wang adaptive fuzzy systems and control. Fuzzy logic controllers are in general considered being. Leonid rezniks fuzzy controllers is unlike any other book on fuzzy control.
This paper proposes a new adaptive tracking fuzzy sliding mode controller for nonlinear systems in the presence of fuzzy compensation. In indirect adaptive fuzzy control, there is an identi. An inputdriven filter is designed for estimating the unmeasured states. Adaptive fuzzy reliable tracking control for a class of uncertain nonlinear timedelay systems with abrupt nonaffine faults changjiang xi, jiuxiang dong pages 100114. Adaptive fuzzy slidingmode control based on generalized ts. Adaptive fuzzy control for fractionalorder interconnected. It does so with a minimum of mathematics and a surfeit of examples, illustrations. This paper proposes an adaptive fuzzy prescribed performance control ppc method of a class of uncertain nonlinear systems. The book also provides rigorous analysis of nonlinear fuzzy control systems, and outlines a simple method to guarantee the stability of nonlinear control systems. An application of fuzzy systems to nonlinear system adaptive control design is proposed in this paper. The developed adaptive fuzzy system was implemented as an identifier of dynamical systems.
Apr 15, 2020 fuzzy adaptive faulttolerant control of multiagent systems with interactions between physical coupling graph and communication graph liang zhao, guanghong yang pages 2038. Stable direct adaptive fuzzy model reference control of. Fuzzy adaptive control of a class of nonlinear systems. Pdf available in journal of engineering technology 204. In this study, the problem of filteringbased adaptive fuzzy control is investigated for nonlinear strictfeedback systems with unmeasured states. C 3department of electrical engineering, national ilan.
In fact, various fuzzy adaptive control schemes, which incorporate fuzzy systems into adaptive control schemes, have already been proposed in the literature 1114. A course in fuzzy systems and control pdf free download epdf. In indirect adaptive fuzzy control, the fuzzy logic systems are. The proposed system uses an adaptation of the slope of the. Fuzzy controllers can be made to adapt to changing process and environment dynamics. This omega engineering white paper explores both the weaknesses of pid systems and the potential benefits of fuzzy logic, with particular reference to issues in temperature control.
Passino, senior member, ieee abstract adaptive control for nonlinear timevarying systems is of both theoretical and practical importance. Control of rotational molding using adaptive fuzzy systems. This paper investigates the tracking control problem for a class of pure. Apr 27, 2007 fuzzy controllers can be made to adapt to changing process and environment dynamics. Adaptive neuralfuzzy control for interpolated nonlinear. Research article adaptive fuzzy sliding mode tracking control. By utilizing the razumikhin functional approach and fuzzy backstepping technique, a novel direct adaptive fuzzy controller is proposed. The membership functions associated with the process controller output are adjusted in response to future or past performance of the feedback control system. Different from the traditional ppc approach that requires the exact values of the initial conditions, by using a new type of performance function, the proposed ppc scheme together with a composite adaptation law works effectively even without the knowledge of initial.
Adaptive fuzzy controller is designed with some adjustable parameters along with an embedded mechanism for adjusting them. Direct adaptive fuzzy control for nonlinear systems with. Composite adaptive fuzzy prescribed performance control of. Adaptive neural fuzzy control for interpolated nonlinear systems yixin diao and kevin m. In order to obtain the controlled objects better tracking performance within the reference signals boundary region, an adaptive fuzzy slidingmode controller is designed aiming at the uncertain secondorder nonlinear system. Robust adaptive fuzzy control of uncertain nonlinear systems. Sliding mode control with adaptive fuzzy compensation for. The fuzzy system is constructed to approximate the nonlinear. The architecture and learning procedure underlying anfis adaptivenetworkbased fuzzy inference system is presented, which is a fuzzy inference system implemented in the framework of adaptive networks. A course infuzzylixin wang a course in fuzzy systems and control lixin wangprenticehall international, inc. Pid with fuzzy logic adaptive controlthe best of both worlds. Simplified filteringbased adaptive fuzzy dynamic surface. A systematic design procedure for fuzzy linguistic controllers with adaptive or learning capability is introduced. In an effort to improve performance, some instrumentation manufacturers are exploring the value of using fuzzy logic for process control.
Sun q, li r and zhang p 2019 stable and optimal adaptive fuzzy control of complex systems using fuzzy dynamic model, fuzzy sets and systems, 3. Recently, the combination of fuzzy control and sliding mode control has become the focus of current research. It shows, step by step, how to combine linguistics and numerical information using various kinds of adaptive fuzzy systems. In this chapter, we will discuss what is an adaptive fuzzy controller and how it works.
One methodology to adapt the initial knowledge base to changing operating conditions is presented. We consider the feedback control system in the crisp. An adaptive neurofuzzy inference system or adaptive networkbased fuzzy inference system anfis is a kind of artificial neural network that is based on takagisugeno fuzzy inference system. Robust adaptive fuzzy control of uncertain nonlinear. Fuzzy logic is viewed as a powerful tool in providing accurate approximation of systems with uncertainties. Stable adaptive fuzzy controllers with application to. The idea of this kind of adaptive control is to directly cancel nonlinear. Fuzzy systems for control applications engineering. Adaptive fuzzy logic control for a class of unknown. Generally, these techniques can be split into two categories. However, the main methods for the robust control are sliding mode control, fuzzy control, and other intelligent controllers. The fuzzy learning system with the training algorithm is called the adaptive fuzzy system. The control goal is that the plant output follows the output y m of the reference model. According to the universal approximation theorem, fuzzy logic systems fls are capable of uniformly approximating any nonlinear function over a compact set to.
By using a hybrid learning procedure, the proposed anfis can construct an inputoutput mapping based on both human knowledge in the form of fuzzy ifthen rules and stipulated. Fuzzy sliding mode control as a robust and intelligent nonlinear control technique is proposed to control processes with severe nonlinearity and unknown models. Pid with fuzzy logic adaptive controlthe best of both worlds technology overview proportional integral derivative pid control is a well established way of driving a system towards a target position or level. Let us now discuss the basic steps for implementing adaptive algorithm. In its own highly informal, idiosyncractic and yet very effective way, it succeeds in providing the reader with a wealth of information about fuzzy controllers. This paper deals with direct adaptive fuzzy control for uncertain affine nonlinear descriptor systems. Fuzzy adaptive faulttolerant control of multiagent systems with interactions between physical coupling graph and communication graph liang zhao, guanghong yang pages 2038. Pdf control of rotational molding using adaptive fuzzy. In this study, due to the nonlinearity of dead zone and uncertainties, the indirect adaptive fuzzy control scheme is adopted to tackle the. Adaptive neuralfuzzy control for interpolated nonlinear systems yixin diao and kevin m. The proposed methodology exploits the power of adaptive control theory to find a lyapunovbased adaptation law for flss. Abstruct an adaptive fuzzy controller is constructed from.
Oct 22, 2019 this paper deals with direct adaptive fuzzy control for uncertain affine nonlinear descriptor systems. In this paper, a stability analysis is suggested for adaptive fuzzy logic systems flss without the requirement of states measurement or estimation. The main contribution of the proposed method is that the fuzzy system is used to realize the. Adaptive fuzzy tracking control of nonlinear systems songshyong chen1, yuanchang chang 2, chen chia chuang3, chauchung song4 and shunfeng su5 1department of information networking technology, hsiuping institute of technology, taiwan, r. A fuzzy control system is a control system based on fuzzy logica mathematical system that analyzes analog input values in terms of logical variables that take on continuous values between 0 and 1, in contrast to classical or digital logic, which operates on discrete values of either 1 or 0 true or false, respectively. The architecture and learning procedure underlying anfis adaptive networkbased fuzzy inference system is presented, which is a fuzzy inference system implemented in the framework of adaptive networks. Adaptive fuzzy control design martin kratmuller siemens pse sro slovakia dubravska cesta 4, 845 37 bratislava, slovak republic email.
Adaptive fuzzy logic control for a class of unknown nonlinear. In this paper, we propose an adaptive control methodology for a class of nonlinear systems with a timevarying. Design and implementation of adaptive fuzzy controller for. A robust fuzzy adaptive law for evolving control systems. Adaptive controller has been used for improving the performance of controller. It summarizes the stateoftheart methods for automatic tuning of the parameters and structures of fuzzy logic systems, and shows both the details of how to apply them to a variety of control and signal processing problems, and how to analyze the performance of the resulting systems. Senior member, ieee abstract advances in nonlinear control theory have provided. Direct adaptive fuzzy control of nonlinear descriptor systems. By using a hybrid learning procedure, the proposed anfis can construct an inputoutput. Adaptive fuzzy systems and control acm digital library. Those approaches are based on the idea proposed by wang 11. The fourth chapters 1622 and fifth chapters 2326 parts concentrate on fuzzy control, where part iv studies nonadaptive fuzzy control and part v studies adaptive fuzzy control. The useful properties of the fuzzy basis functions and membership are explored to be used for stability analysis, and an alternative lyapunov function depending on both control input and system state is utilized.
Design and implementation of adaptive fuzzy controller for speed control of brushless dc motors abstract this paper presents the design and implementation of an adaptive fuzzy logic controller for the speed control of brushless dc motors. After taking account of the control sensitivitys requirement for the membership function, the controller capitalizes on the generalized membership functions. Uang h and chen b 2019 robust adaptive optimal tracking design for uncertain missile systems, fuzzy sets and systems, 126. Adaptive fuzzy system modeling article pdf available in journal of engineering technology 204. Fuzzy control 1 1 fuzzy sets, logic and control 3 1. Mar 21, 2016 in this study, the problem of filteringbased adaptive fuzzy control is investigated for nonlinear strictfeedback systems with unmeasured states. Abstractthis paper describes an adaptive fuzzy control algorithm that may be.
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