Adaptive Fuzzy Sliding Mode Control Design Lyapunov Approach (original) (raw)
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Adaptive fuzzy sliding mode control scheme for uncertain systems
Communications in Nonlinear Science and Numerical Simulation, 2009
Most physical systems inherently contain nonlinearities which are commonly unknown to the system designer. Therefore, in modeling and analysis of such dynamic systems, one needs to handle unknown nonlinearities and/or uncertain parameters. This paper proposes a new adaptive tracking fuzzy sliding mode controller for a class of nonlinear systems in the presence of uncertainties and external disturbances. The main contribution of the proposed method is that the structure of the controlled system is partially unknown and does not require the bounds of uncertainty and disturbance of the system to be known; meanwhile, the chattering phenomenon that frequently appears in the conventional variable structure systems is also eliminated without deteriorating the system robustness. The performance of the proposed approach is evaluated for two well-known benchmark problems. The simulation results illustrate the effectiveness of our proposed controller.
Adaptive Fuzzy Sliding Mode Control for Uncertain Nonlinear Systems
International Journal of Fuzzy Logic and Intelligent Systems, 2011
This paper deals with a new adaptive fuzzy sliding mode controller and its application to an inverted pendulum. We propose a new method of adaptive fuzzy sliding mode control scheme that the fuzzy logic system is used to approximate the unknown system functions in designing the SMC of uncertain nonlinear systems. The controller's construction and its analysis involve sliding modes. The proposed controller consists of two components. Sliding mode component is employed to eliminate the effects of disturbances, while a fuzzy model component equipped with an adaptation mechanism reduces modeling uncertainties by approximating model uncertainties. To demonstrate its performance, the proposed control algorithm is applied to an inverted pendulum. The results show that both alleviation of chattering and performance are achieved.
Analysis on Advancement of Hybrid Fuzzy Sliding Mode Controllers for Nonlinear Systems
arXiv (Cornell University), 2019
Chattering phenomena is the major problem affecting sliding mode control (SMC). Also, finding a suitable structure and appropriate parameters values of fuzzy logic system (FLS) is a complex and difficult task. In addition, the stability of a general FLS is difficult to guarantee. Many types of combinations between FLS and SMC have been used to form an intelligent and robust controller that deviates from the limitations of each constituent and benefit from the advantages of each constituent. In this study, a survey of recent developments on the Hybridization of FLS (type-1) and SMC is presented. In addition, the differences between using the SMC in FLC or using FLC in SMC as well as their limitation and advantages are highlighted. It is found that the majority of the combinations made are intended to approximate the nonlinear sliding surface within the boundary layer. Limitations of the previous approaches and future research directions are pointed out. For novice researchers, this survey can serve as a foundation for their work while for expert researchers this review can serve as a benchmark for further advancement and exploration of other hybridization methods.
Design of Adaptive Sliding Mode Control with Fuzzy Controller and PID Tuning for Uncertain Systems
2017
1PG student, Dept of EEE, Andhra University (A), Visakhapatnam, India 2Assistant Professor, Dept of EEE, Andhra University (A), Visakhapatnam, India ---------------------------------------------------------------------***--------------------------------------------------------------------Abstract – In this paper, a robust control system with the fuzzy sliding mode controller and sliding mode control with PID tuning method for a class of uncertain system is presented. The goal is to achieve system robustness against parameter variations and external disturbances. A Fuzzy logic controller using simple approach & smaller rule set is proposed. Suitable PID control gain parameters can be systematically on-line computed according to the developed adaptive law. To reduce the high frequency chattering in the switching part of the controller, a boundary layer technique is utilized. The proposed method controller is applied to a brushless DC motor control system.
Adaptive fuzzy sliding mode control of uncertain nonlinear systems
Saude E Sociedade, 2010
This paper presents a detailed discussion about the convergence properties of a variable structure controller for uncertain single-input-single-output nonlinear systems (SISO). The adopted approach is based on the sliding mode control strategy and enhanced by an adaptive fuzzy algorithm to cope with modeling inaccuracies and external disturbances that can arise. The boundedness of all closed-loop signals and the convergence properties of the tracking error are analytically proven using Lyapunov's direct method and Barbalat's lemma. This result corrects flawed conclusions previously reached in the literature. An application of this adaptive fuzzy sliding mode controller to a second-order nonlinear system is also presented. The obtained numerical results demonstrate the improved control system performance.
Use of adaptive fuzzy systems in parameter tuning of sliding-mode controllers
IEEE/ASME Transactions on Mechatronics, 2001
Soft computing methodologies, when used in combination with sliding-mode control (SMC) systems, aim to alleviate implementation difficulties of SMCs or to intelligently tune the controller parameters. In this paper, it is proposed to combine adaptive fuzzy systems with SMCs to solve the chattering problem of sliding-mode control for robotic applications. In the design of the controller, special attention is paid to chattering elimination without a degradation of the tracking performance. Furthermore, the a priori knowledge required about the system dynamics for design is kept to a minimum. The paper starts with a consideration of basic principles of sliding-mode and fuzzy controllers. Implementation difficulties and most popular solutions are then overviewed. Next, the design of a SMC reported in the literature is outlined and guidelines for the selection of controller parameters for the best tracking performance without chattering are presented. A novel approach based on the introduction of a "chattering variable" is developed. This variable, as a measure of chattering, is used as an input to an adaptive fuzzy system responsible for ringing minimization. On-line tuning of parameters by fuzzy rules is carried out for the SMC and experimental results are presented. Conclusions are presented lastly.
Adaptive Interval Type-2 Fuzzy Sliding Mode Control for Nonlinear Uncertain Systems
In this paper, by using a combination of fuzzy identification and the sliding mode control, a novel adaptive interval type-2 fuzzy sliding mode control is proposed for unknown non linear system. The AIT2FSMC system is constructing of a fuzzy control design and a hitting Control design. In the first, an interval type 2 fuzzy controller is designed to affect a feed-back linearization (FL) control law. In the second, a hitting controller is designed to compensate the approximation error between the FL control law and the interval type-2 fuzzy controller. The parameters of the interval type-2 fuzzy controller, as well as the uncertainty bound of the approximation error, are tuned adaptively. The adaptive laws are derived in the sense of Lyapunov stability theorem, thus the stability of the system can be guaranteed. Two examples illustrate the feasibility of the proposed method.
An Adaptive Fuzzy Sliding Mode Control Scheme for Robotic Systems
Intelligent Control and Automation, 2011
In this article, an adaptive fuzzy sliding mode control (AFSMC) scheme is derived for robotic systems. In the AFSMC design, the sliding mode control (SMC) concept is combined with fuzzy control strategy to obtain a model-free fuzzy sliding mode control. The equivalent controller has been substituted for by a fuzzy system and the uncertainties are estimated on-line. The approach of the AFSMC has the learning ability to generate the fuzzy control actions and adaptively compensates for the uncertainties. Despite the high nonlinearity and coupling effects, the control input of the proposed control algorithm has been decoupled leading to a simplified control mechanism for robotic systems. Simulations have been carried out on a two link planar robot. Results show the effectiveness of the proposed control system.
Design a new sliding mode adaptive hybrid fuzzy controller
Journal of Advanced Science & Engineering Research, 1 (1): 115-123, 2011
One of the most important challenges in nonlinear, multi-input multi-output (MIMO) and time variant systems (e.g., robot manipulator) is designing a controller with acceptable performance. This paper focuses on design a new sliding mode on-line tunable gain hybrid fuzzy control (SMHFLC) applied in the robot manipulator. The PD fuzzy controller is designed as 49 rules Mamdani’s error based which the integral error controller is added to the fuzzy controller to get the better performance. One of the most important robust non linear methodologies is sliding mode method. On-line tuning is used in systems with various dynamic parameters, structure and unstructured uncertainties and need to be training on line. Therefore combined adaptive method and hybrid PD fuzzy controllers can solve the uncertainty challenge in nonlinear systems.
International Journal of Engineering, 5 (5):360-379, 2011
In this research, an artificial chattering free adaptive fuzzy sliding mode control design and application to uncertain robotic manipulator has proposed in order to design high performance nonlinear controller in the presence of uncertainties. Regarding to the positive points in sliding mode controller, fuzzy logic controller and adaptive method, the output has improved. Each method by adding to the previous controller has covered negative points. The main target in this research is design of model free estimator on-line sliding mode fuzzy algorithm for robot manipulator to reach an acceptable performance. Robot manipulators are highly nonlinear, and a number of parameters are uncertain, therefore design model free controller using both analytical and empirical paradigms are the main goal. Although classical sliding mode methodology has acceptable performance with known dynamic parameters such as stability and robustness but there are two important disadvantages as below: chattering phenomenon and mathematical nonlinear dynamic equivalent controller part. To solve the chattering fuzzy logic inference applied instead of dead zone function. To solve the equivalent problems in classical sliding mode controller this paper focuses on applied fuzzy logic method in classical controller. This algorithm works very well in certain environment but in uncertain or various dynamic parameters, it has slight chattering phenomenon. The system performance in sliding mode controller and fuzzy sliding mode controller are sensitive to the sliding function. Therefore, compute the optimum value of sliding function for a system is the next challenge. This problem has solved by adjusting sliding function of the adaptive method continuously in real-time. In this way, the overall system performance has improved with respect to the classical sliding mode controller. This controller solved chattering phenomenon as well as mathematical nonlinear equivalent part by applied fuzzy supervisory method in sliding mode fuzzy controller and tuning the sliding function.