Ming-Ying Hsiao

Design of interval type-2 fuzzy sliding-mode controller

In this paper, an interval type-2 fuzzy sliding-mode controller (IT2FSMC) is proposed for linear and nonlinear systems. The proposed IT2FSMC is a combination of the interval type-2 fuzzy logic control (IT2FLC) and the sliding-mode control (SMC) which inherits the benefits of these two methods. The objective of the controller is to allow the system to move to the sliding surface and remain in on it so as to ensure the asymptotic stability of the closed-loop system. The Lyapunov stability method is adopted to verify the stability of the interval type-2 fuzzy sliding-mode controller system. The design procedure of the IT2FSMC is explored in detail. A typical second order linear interval system with 50% parameter variations, an inverted pendulum with variation of pole characteristics, and a Duffing forced oscillation with uncertainty and disturbance are adopted to illustrate the validity of the proposed method. The simulation results show that the IT2FSMC achieves the best tracking performance in comparison with the type-1 Fuzzy logic controller (T1FLC), the IT2FLC, and the type-1 fuzzy sliding-mode controller (T1FSMC).

Robust

The main theme of this paper is to present robust fuzzy controllers for a class of discrete fuzzy bilinear systems. First, the parallel distributed compensation method is utilized to design a fuzzy controller, which ensures the robust asymptotic stability of the closed-loop system and guarantees an Hinfin norm-bound constraint on disturbance attenuation for all admissible uncertainties. Second, based on the Schur complement and some variable transformations, the stability conditions of the overall fuzzy control system are formulated by linear matrix inequalities. Finally, the validity and applicability of the proposed schemes are demonstrated by a numerical simulation and the Van de Vusse example.

H_{\infty}

An increasing number of carlike mobile robot (CLMR) studies have addressed the issues of autonomous parking and obstacle avoidance. An autonomous parking controller can provide convenience to a novice driver. However, if the controller is not designed adequately, it may endanger the car and the driver. Therefore, this paper presents a novel multifunctional intelligent autonomous parking controller that is capable of effectively parking the CLMR in an appropriate parking space, by integrating sensor data capable of obtaining the surrounding data of the robot. An ultrasonic sensor array system has been developed with group-sensor firing intervals. A binaural approach to the CLMR has been adopted for providing complete contactless sensory coverage of the entire workspace. The proposed heuristic controller can obtain the posture of a mobile robot in a parking space. In addition, the controller can ensure the ability of the CLMR to withstand collision to guarantee safe parking. Moreover, the CLMR can recognize the parking space and the obstacle position in dynamic environment. Therefore, the proposed controller installed in a car could ensure safe driving. Finally, practical experiments demonstrate that the proposed multifunctional intelligent autonomous parking controllers are feasible and effective.

Fuzzy Control for a Class of Uncertain Discrete Fuzzy Bilinear Systems

In this paper, a decoupled interval type-2 fuzzy sliding-mode controller (IT2FSMC) is proposed for controlling a time-varying unified chaotic system. This technique, a fusion of the interval type-2 fuzzy logic control (IT2FLC) method and the sliding-mode control (SMC) method, inherits the benefits of both methods. In the sense of Lyapunov stability, the objective of the proposed controller is to assure the system approaching to the asymptotic stability of the closed-loop controlled system. The simulations include regulating the states of a time-varying unified chaotic system to the origin and tracking a predefined orbit extracted from the unforced Chens chaotic system. The simulation results, from the viewpoint of the integral of the absolute error (IAE), the integral of time multiplied by the absolute error (ITAE), and the integral of square error (ISE), demonstrate that the IT2FSMC can achieve better control performance in comparison with that of the conventional fuzzy sliding-mode control (FSMC).

Multifunctional Intelligent Autonomous Parking Controllers for Carlike Mobile Robots

A combined intelligent technique is proposed for controlling the trajectory-tracking of a nonholonomic wheeled mobile robot (WMR), which comprises kinematic control and an interval type-2 adaptive fuzzy sliding-mode dynamic control (IT2-AFSMDC). The kinematic model is introduced first, and then the control gains can be obtained from the back-stepping method as the input of the dynamic model. The IT2-AFSMDC is propounded for the dynamic part, a combination of the interval type-2 fuzzy logic control (IT2-FLC) and the adaptive fuzzy sliding-mode dynamic control (AFSMDC), which inherits the benefits of these two methods, and adaptive law is introduced to cope with the uncertainties and disturbances of the system. The trajectory-tracking stability is proved by the Lyapunov stability analysis. Computer simulations demonstrate the validity of the proposed method. The simulation results show that the tracking performance of the IT2-AFSMDC is better than that of the AFSMDC. SMC techniques [5, 14] provide discontinuous control laws to drive the system states to a specified sliding surface and to keep them on the sliding surface. The dynamic performance of the SMC has been adopted as an effective robust control approach for the problems of system uncertainties and external disturbances. But there still are some drawbacks in the SMC; for example, chattering characteristics occur when the system dynamics is close to the sliding surface. This problem should be eliminated or alleviated. The FSMC [15-16], a hybrid of the SMC and FLC, gives a simple way to design the controller systematically and provides the asymptotical stability of the system. In general, the FSMC can also reduce the rule number in the FLC and still possess robustness.

Controlling a Time-Varying Unified Chaotic System via Interval Type 2 Fuzzy Sliding-Mode Technique

The robust //„ fuzzy controller design problem is studied for a class of time-delay fuzzy bilinear systems (FBSs) with an additive disturbance in this paper. The parallel distributed compensation (PDC) method is adopted to design a fuzzy controller which ensures the robust asymptotic stability of the time-delay FBS with an additive disturbance and guarantees an //„ norm bound constraint on disturbance attenuation. Utilizing the Schur complement and some variable transformations, the stability conditions of the overall fuzzy control system are formulated in the form of linear matrix inequalities (LMIs). Finally, the validity and effectiveness of the proposed schemes are demonstrated by simulations.

Interval Type-2 Adaptive Fuzzy Sliding-Mode Dynamic Control Design for Wheeled Mobile Robots

In this paper, we propose a novel interval type-2 fuzzy logic controller (IT2FLC) for interval system. The precise mathematical model of the controlled plant is not required to design this IT2FLC. Design procedure of the IT2FLC is explored in detail. A typical linear interval system with 50% parameter variations is adopted to demonstrate the effectiveness of the proposed IT2FLC. For better understanding the performance of IT2FLC, numerous shapes of membership functions and variation of rule numbers of rule table are evaluated for simulation thoroughly. The simulation results are compared with those from type-1 fuzzy logic controller (T1FLC) under same conditions. It shows that the performance of IT2FLC is much better than that of T1FLC if the number of rule is reduced.

Robust Η-infinity Fuzzy Control for a Class of Time-Delay Fuzzy Bilinear Systems with an Additive Disturbance

This paper presents a robust H∞ fuzzy controller for a class of T-S time-delay discrete fuzzy bilinear system (DFBS). Firstly, a discrete robust H∞ fuzzy controller is proposed to stabilize the T-S time-delay DFBS with disturbance. Secondly, based on the Schur complement and some variable transformation, the stability conditions of the overall fuzzy control system are formulated by linear matrix inequalities (LMIs). Finally, a numerical example is utilized to demonstrate the validity and effectiveness of the proposed control scheme.