Adaptive fuzzy sliding mode control scheme for uncertain systems (original) (raw)
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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.
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.
Adaptive Fuzzy Sliding Mode Control Design Lyapunov Approach
An adaptive fuzzy sliding mode control algorithm is proposed for a class of continuous time unknown nonlinear systems. In contrast to the existing sliding mode control (SMC) design, where the presence of hitting control may introduce problems to controlled systems, the proposed adaptive fuzzy logic controller takes advantages of both SMC and proportional integral (PI) control. The chattering action is attenuated and robust performance can be ensured. The stability analysis for the proposed control algorithm is provided. Two nonlinear system simulation examples are presented to verify the effectiveness of the proposed method.
This paper presents controlling of a class of nonlinear systems with structured and unstructured uncertainties using fuzzy sliding mode control. First known dynamics of the system are eliminated through feedback linearization and then fuzzy sliding mode controller is designed using TS method, based on the Lyapunov method, which is capable of handling uncertainties. There are no signs of the undesired chattering phenomenon in the proposed method. The globally asymptotic stability of the closed-loop system is mathematically proved. Finally, this method of control is applied to the inverted pendulum system as a case study. Simulation results show the system performance is desirable.
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.
A novel sliding mode controller scheme for a class of nonlinear uncertain systems
International Journal of Modelling, Identification and Control, 2018
This paper considers a continuous sliding mode control for a class of nonlinear systems with uncertainties including both parameter variations and external disturbances. Under the framework of sliding mode and using the upper bounds of the uncertainties, the proposed controller is derived to guarantee the stability of an overall closed-loop system and ensure robustness against modelling errors, parameter uncertainties and external disturbances. As for chattering elimination in sliding mode control, a boundary layer around the sliding surface is used and the continuous control is applied within the boundary. Moreover, an extended schema of a higher-order sliding mode controller is developed in this paper as another solution to avoid the problem of chattering effect. Simulation results demonstrate the efficacy of the proposed control methodology to stabilise an inverted pendulum, which is a standard nonlinear benchmark system. The applicability of the proposed algorithm will be extended, via suitable modifications, to the case of multivariable nonlinear systems with uncertainties of more general type, covering a wide class of processes.
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.
2003
A novel adaptive fuzzy sliding mode control design is developed for trajectory tracking of a class of nonlinear systems in this paper. This control design uses the modelling error to adaptively estimate the deterministic uncertainties as well as the control gain based on the fuzzy systems approach. By this design, the bounds of the uncertainties are not required to be known in advance, and the robust stability of closed loop systems is analysed in the Lyapunov sense. Simulation results are given to demonstrate the improved performance.
IEEE Transactions on Automatic Control, 2000
In this paper, a combined adaptive/variable structure control approach is presented that exploits the good properties of the backstepping procedure and of a second-order sliding-mode control algorithm. This algorithm enables one to attain the conditions = 0, _ = 0 (second-order sliding mode) in a finite time, = 0 being a predefined sliding manifold. The combined approach retains the stability and convergence features of the original adaptive strategy. In addition, it allows one to deal with systems with uncertainties of more general types, ensuring robustness, as well as a reduction in the computational load.