Tzuu-Hseng S. Li

Implementation of human-like driving skills by autonomous fuzzy behavior control on an FPGA-based car-like mobile robot

In this paper, the concepts of car maneuvers, fuzzy logic control (FLC), and sensor-based behaviors are merged to implement the human-like driving skills by an autonomous car-like mobile robot (CLMR). Four kinds of FLCs, fuzzy wall-following control, fuzzy corner control, fuzzy garage-parking control, and fuzzy parallel-parking control, are synthesized to accomplish the autonomous fuzzy behavior control (AFBC). Computer simulation results illustrate the effectiveness of the proposed control schemes. The setup of the CLMR is provided, where the implementation of the AFBC on a field-programmable gate array chip is also addressed. Finally, the real-time implementation experiments of the CLMR in the test ground demonstrate the feasibility in practical car maneuvers.

Fuzzy target tracking control of autonomous mobile robots by using infrared sensors

The theme of this paper is to design a real-time fuzzy target tracking control scheme for autonomous mobile robots by using infrared sensors. At first two mobile robots are setup in the target tracking problem, where one is the target mobile robot with infrared transmitters and the other one is the tracker mobile robot with infrared receivers and reflective sensors. The former is designed to drive in a specific trajectory. The latter is designed to track the target mobile robot. Then we address the design of the fuzzy target tracking control unit, which consists of a behavior network and a gate network. The behavior network possesses the fuzzy wall following control (FWFC) mode, fuzzy target tracking control (FTTC) mode, and two fixed control modes to deal with different situations in real applications. Both the FWFC and FTTC are realized by the fuzzy sliding-mode control scheme. A gate network is used to address the fusion of measurements of two infrared sensors and is developed to recognize which situation is belonged to and which action should be executed. Moreover, the target tracking control with obstacle avoidance is also investigated in this paper. Both computer simulations and real-time implementation experiments of autonomous target tracking control demonstrate the effectiveness and feasibility of the proposed control schemes.

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).

T–S Fuzzy Bilinear Model and Fuzzy Controller Design for a Class of Nonlinear Systems

This paper proposes a fuzzy bilinear model for a class of nonlinear systems and a fuzzy controller to stabilize such systems. By examination of a modeling problem, we describe how to transform a nonlinear system into a bilinear one via Taylors series expansion and then we adopt the Takagi-Sugeno (T-S) fuzzy modeling technique to construct a fuzzy bilinear model. For controller design, the parallel distributed compensation (PDC) method is utilized to stabilize the fuzzy bilinear system (FBS), and some sufficient conditions are derived to guarantee the stability of the overall fuzzy control system via linear matrix inequalities (LMIs). Moreover, we propound some sufficient conditions for robust stabilization of the FBS with parametric uncertainties. Finally, a numerical example and the Van de Vusse model are utilized to demonstrate the validity and effectiveness of the proposed FBS.

Autonomous fuzzy parking control of a car-like mobile robot

This paper is devoted to design and implement a car-like mobile robot (CLMR) that possesses autonomous garage-parking and parallel-parking capability by using real-time image processing. For fuzzy garage-parking control (FGPC) and fuzzy parallel-parking control (FPPC), feasible reference trajectories are provided for the fuzzy logic controller to maneuver the steering angle of the CLMR. We propose two FGPC methods and two FPPC methods to back-drive or head-in the CLMR to the garage and the parking lot, respectively. Simulation results illustrate the effectiveness of the developed schemes. The overall experimental setup of the parking system developed in this paper is composed of a host computer, a communication module, a CLMR, and a vision system. Finally, the image-based real-time implementation experiments of the CLMR demonstrate the feasibility and effectiveness of the proposed schemes.

GA-based fuzzy PI/PD controller for automotive active suspension system

A genetic-algorithm (GA)-based fuzzy proportional-plus-integral-proportional-plus-derivative (PI/PD) controller is proposed for an automotive active suspension system (AASS). The fuzzy PI- and PD-type controllers are combined to cope with the different road conditions. By using the merit of GAs, the optimal decision-making rules for both types of controllers are constructed. The real-time simulation results demonstrate that the fusion of GAs and fuzzy controller for an AASS can provide passengers much more ride comfort.

MIMO adaptive fuzzy terminal sliding-mode controller for robotic manipulators

In this paper, a new fuzzy terminal sliding-mode controller (FTSMC) is developed for robotic manipulators. A terminal sliding mode controller can drive the system tracking errors to converge to zero in finite time and the closed-loop system is infinitely stable. The FTSMC, incorporating the fuzzy logic controller and the terminal sliding-mode controller, is designed to retain the advantages of the terminal sliding-mode controller and to reduce the chattering. The simulation results show that the FTSMC can provide much good tracking performance than that of the classical fuzzy sliding-mode controller (FSMC).

EP-based kinematic control and adaptive fuzzy sliding-mode dynamic control for wheeled mobile robots

This paper proposes a complete control law comprising an evolutionary programming based kinematic control (EPKC) and an adaptive fuzzy sliding-mode dynamic control (AFSMDC) for the trajectory-tracking control of nonholonomic wheeled mobile robots (WMRs). The control gains for kinematic control (KC) are trained by evolutionary programming (EP). The proposed AFSMDC not only eliminates the chattering phenomenon in the sliding-mode control, but also copes with the system uncertainties and external disturbances. Additionally, the convergence of trajectory-tracking errors is proved by the Lyapunov stability theory. Computer simulations are presented to confirm the effectiveness of the proposed complete control law. Finally, real-time experiments are done in the test field to demonstrate the feasibility of real WMR maneuvers.

An approach to systematic design of the fuzzy control system

Abstract This paper presents a new design method of fuzzy control system (FCS). The concept from the sliding mode control is adopted to construct fuzzy control scheme. If the original control rules are inappropriate, the adaptive mechanism will modify these rules according to the proposed algorithms. In particular, the structure of sliding surface provides a reasonable estimation to the universes of discourse on which the fuzzy control rules are based. Finally, an inverted pendulum system is used to demonstrate the availability of the proposed approaches.

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.