This paper investigates the problem of adaptive integral sliding mode control for general Takagi–Sugeno fuzzy systems with matched uncertainties and its applications. Different control input matrices are allowed in fuzzy systems. The matched uncertainty is modeled in a unified form, which can be handled by the adaptive methodology. A fuzzy integral-type sliding surface is utilized and the parameter matrices can be determined according to user's requirement. Based on the designed sliding surface, a new sliding mode controller is proposed, and the structure of the controller depends on the difference between the disturbance input matrices and the control input matrices. It is shown that under the proposed sliding mode controller, the resulting closed-loop system can achieve the uniformly ultimate boundedness. Furthermore, simulation examples are presented to show the merit and applicability of the proposed fuzzy sliding mode control method.

Adaptive Sliding Mode Control for Takagi–Sugeno Fuzzy Systems and Its Applications

This paper is concerned with the problem of nonfragile H∞ filtering for continuous-time Takagi-Sugeno (T-S) fuzzy systems. The filter to be designed is assumed to have two types of multiplicative gain variations. First, two relaxed H∞ filtering analysis conditions are proposed based on useful linear matrix inequality preliminaries. Whereafter, the results are exploited to derive sufficient conditions for designing a nonfragile H∞ filter, which guarantees a prescribed H∞ performance of the filtering error system. Compared with the existing results, the proposed design methods not only suit for a standard form of the fuzzy filter but also give more relaxed design conditions. Finally, simulation examples will be given to show the efficiency of the proposed design methods.

Nonfragile $H_{\infty}$ Filter Design for T–S Fuzzy Systems in Standard Form

This paper addresses the problems of observer-based fault reconstruction and fault-tolerant control for Takagi–Sugeno fuzzy descriptor systems subject to time delays and external disturbances. A novel fuzzy descriptor learning observer is constructed to achieve simultaneous reconstruction of system states and actuator faults. Sufficient conditions for the existence of the proposed observer are explicitly provided. Utilizing the reconstructed fault information, a reconfigurable fuzzy fault-tolerant controller based on the separation property is designed to compensate for the impact of actuator faults on system performance by stabilizing the closed-loop system. In addition, the design of the fault reconstruction observer and the fault-tolerant controller is formulated in terms of linear matrix inequalities that can be conveniently solved using convex optimization techniques. Finally, simulation results on a truck–trailer system are presented to verify the effectiveness of the proposed approaches.

Fault Reconstruction and Fault-Tolerant Control via Learning Observers in Takagi–Sugeno Fuzzy Descriptor Systems With Time Delays

This paper is concerned with the problems of state and output feedback control for interval type-2 (IT2) fuzzy systems with mismatched membership functions. The IT2 fuzzy model and the IT2 state and output feedback controllers do not share the same membership functions. A novel performance index, which is expressed as an extended dissipativity performance, is introduced to be a generalization of $H_{\infty }$ , $L_{2}$ – $L_{\infty }$ , passive, and dissipativity performances indexes. First, the IT2 Takagi–Sugeno fuzzy model and the controllers are constructed by considering the mismatched membership functions. Second, on the basis of Lyapunov stability theory, the IT2 fuzzy state and output feedback controllers are designed, respectively, to guarantee that the closed-loop system is asymptotically stable with extended dissipativity performance. The existence conditions of the two kinds of controllers are obtained in terms of convex optimization problems, which can be solved by standard software. Finally, simulation results are provided to illustrate the effectiveness of the proposed methods.

/pdf/state-and-output-feedback-control-of-interval-type-2-fuzzy-48ngxbiwaf.pdf

State and Output Feedback Control of Interval Type-2 Fuzzy Systems With Mismatched Membership Functions

Underactuated robotics is an emerging research direction in the field of robotics. The control input of the underactuated robot is less than the degree of freedom of the system. It has the advantag...

https://journals.sagepub.com/doi/pdf/10.1177/1729881419862164

Underactuated robotics: A review:

In this paper, the balance control of a ball and beam system is considered. Based on the T-S fuzzy modeling, the dynamic model of the ball and beam system is formulated as a strict feedback form with modeling errors. Then, an adaptive dynamic surface control (DSC) is utilized to achieve the goal of ball positioning subject to parameter uncertainties. The robust stability of the closed-loop system is preserved by using the Lyapunov theorem. In addition to simulation results, the proposed T-S fuzzy model-based adaptive dynamic surface controller is applied to a real ball and beam system for practical evaluations. Simulation and experimental results illustrate that the proposed control scheme has much better performance than that of conventional DSC. Furthermore, parameter uncertainties and external disturbance are considered to highlight the robustness of the proposed control scheme.

T-S Fuzzy Model-Based Adaptive Dynamic Surface Control for Ball and Beam System

This paper aims to investigate the formation control of leader-follower multiagent systems, where the problem of collision avoidance is considered. Based on the graph-theoretic concepts and locally distributed information, a neural fuzzy formation controller is designed with the capability of online learning. The learning rules of controller parameters can be derived from the gradient descent method. To avoid collisions between neighboring agents, a fuzzy separation controller is proposed such that the local minimum problem can be solved. In order to highlight the advantages of this fuzzy logic based collision-free formation control, both of the static and dynamic leaders are discussed for performance comparisons. Simulation results indicate that the proposed fuzzy formation and separation control can provide better formation responses compared to conventional consensus formation and potential-based collision-avoidance algorithms.

/pdf/fuzzy-formation-control-and-collision-avoidance-for-3jj7u8u7kh.pdf

Fuzzy Formation Control and Collision Avoidance for Multiagent Systems

This paper aims to investigate the formation control of multi-robot systems, where the kinematic model of a differentially driven wheeled mobile robot is considered. Based on the graph-theoretic concepts and locally distributed information, an adaptive neural fuzzy formation controller is designed with the capability of on-line learning. The learning rules of controller parameters can be derived from the analyzing of Lyapunov stability. In addition to simulations, the proposed techniques are applied to an experimental multi-robot platform for performance validations. From simulation and experimental results, the proposed adaptive neural fuzzy protocol can provide better formation responses compared to conventional consensus algorithms.

Adaptive Neuro-Fuzzy Formation Control for Leader-Follower Mobile Robots

This paper presents a new robust adaptive control method for multi-robot systems, where the kinematic model of a differentially driven wheeled mobile robot is considered. Particularly, the situations involving partial loss of actuator effectiveness are addressed. Distributed controllers are derived based on dynamic surface control techniques over networked multiple robots. In addition, adaptive mechanisms are applied to estimate the bounds of effectiveness factor and uncertainty bounds. The robust stability of the multi-robot systems are preserved by using the Lyapunov theorem. The proposed controller can make the robots reach a desired formation following a designate trajectory. Simulation results indicate that the proposed control scheme has superior responses compared to conventional dynamic surface control.

Adaptive dynamic surface control for fault-tolerant multi-robot systems

This paper focuses on the design of a formation controller for multi-robot dynamic systems using adaptive fuzzy terminal sliding-mode techniques. The dynamic model of differential wheeled robots is considered. To achieve finite time leader-follower formation control, a fuzzy terminal sliding-mode controller is derived based on graph theory and consensus algorithm. Moreover, an adaptive law is provided to estimate the bounds of unknown uncertainties. Both simulation and experimental results are applied to validate the formation performance. It is indicated that the proposed adaptive control scheme can provide better leader-following formation responses of networked multiple robots.

Wei-Shou Chan

Papers

T-S Fuzzy Model-Based Adaptive Dynamic Surface Control for Ball and Beam System

Fuzzy Formation Control and Collision Avoidance for Multiagent Systems

Adaptive Neuro-Fuzzy Formation Control for Leader-Follower Mobile Robots

Adaptive dynamic surface control for fault-tolerant multi-robot systems

Leader-following formation control of multi-robot systems with adaptive fuzzy terminal sliding-mode controller