Yeong-Hwa Chang

A Novel Fuzzy-Sliding and Fuzzy-Integral-Sliding Controller for the Twin-Rotor Multi-Input–Multi-Output System

In this paper, a novel fuzzy-sliding and fuzzy-integral-sliding controller (FSFISC) is designed to position the yaw and pitch angles of a twin-rotor multi-input-multi-output system (TRMS). With the coupling effects, which are considered as the uncertainties, the highly coupled nonlinear TRMS is pseudodecomposed into a horizontal subsystem and a vertical subsystem (VS). The proposed FSFISC consists of a fuzzy-sliding controller and an FISC for the horizontal and the VSs, respectively. The reaching conditions and the stability of the TRMS with the proposed controller are guaranteed. Simulation results are included to indicate that TRMS with the presented FSFISC can greatly alleviate the chattering effect and remain robust to the external disturbances. In addition, the performance comparisons with the proportional-integral-differential (PID) approach using a modified real-value-type genetic algorithm are provided to show that the FSFISC has better performance in the aspects of error and control indexes.

Fuzzy Sliding-Mode Formation Control for Multirobot Systems: Design and Implementation

This paper mainly addresses the decentralized formation problems for multiple robots, where a fuzzy sliding-mode formation controller (FSMFC) is proposed. The directed networks of dynamic agents with external disturbances and system uncertainties are discussed in consensus problems. To perform a formation control and to guarantee system robustness, a novel formation algorithm combining the concepts of graph theory and fuzzy sliding-model control is presented. According to the communication topology, formation stability conditions can be determined so that an FSMFC can be derived. By Lyapunov stability theorem, not only the system stability can be guaranteed, but the desired formation pattern of a multirobot system can be also achieved. Simulation results are provided to demonstrate the effectiveness of the provided control scheme. Finally, an experimental setup for the e-puck multirobot system is built. Compared to first-order formation algorithm and fuzzy neural network formation algorithm, it shows that real-time experimental results empirically support the promising performance of desire.

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

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.

Adaptive Dynamic Surface Control for Uncertain Nonlinear Systems With Interval Type-2 Fuzzy Neural Networks

This paper presents a new robust adaptive control method for a class of nonlinear systems subject to uncertainties. The proposed approach is based on an adaptive dynamic surface control, where the system uncertainties are approximately modeled by interval type-2 fuzzy neural networks. In this paper, the robust stability of the closed-loop system is guaranteed by the Lyapunov theorem, and all error signals are shown to be uniformly ultimately bounded. In addition to simulations, the proposed method is applied to a real ball-and-beam system for performance evaluations. To highlight the system robustness, different initial settings of ball-and-beam parameters are considered. Simulation and experimental results indicate that the proposed control scheme has superior responses, compared to conventional dynamic surface control.

Simplified type-2 fuzzy sliding controller for wing rock system

Wing rock is a highly nonlinear phenomenon in which aircrafts with slender delta wings undergo limit cycle roll oscillations at high angles of attack. A simplified type-2 fuzzy sliding controller is designed for suppressing wing rock phenomena and tracking the desired trajectories. To reduce the computational complexity of a type-reducer, the end points of a type-reduced set are approximated by the outputs of two standard fuzzy sliding mechanisms in the proposed simplified type-2 fuzzy sliding controller. Furthermore, the sliding modes of the fuzzy sliding control system are guaranteed. Simulation results are included to show the effectiveness of the proposed simplified type-2 fuzzy sliding controller.

Fuzzy sliding-mode control for ball and beam system with fuzzy ant colony optimization

This paper mainly addresses the balance control of a ball and beam system, where a pair of decoupled fuzzy sliding-mode controllers (DFSMCs) are proposed. The DFSMC has the advantage of reducing the design complexity, in which the coupling dynamics of the state-error dynamics are considered as disturbance terms. Stability analysis of the ball and beam system with DFSMCs is also discussed in detail. To further improve the control performance, an improved ant colony optimization (ACO) is proposed to optimize the controller parameters. The proposed ACO algorithm has the enhanced capability of fuzzy pheromone updating and adaptive parameter tuning. The proposed ACO-optimized scheme is utilized to tune the parameters of the fuzzy sliding-mode controllers for a real ball-and-beam system. Compared to some conventional ACO algorithms, simulation and experimental results all indicate that the proposed scheme can provide better performance in the aspect of convergence rate and accuracy.

Fuzzy Swing-Up and Fuzzy Sliding-Mode Balance Control for a Planetary-Gear-Type Inverted Pendulum

An energy-compensated fuzzy swing-up and balance control is investigated for the planetary-gear-type inverted pendulum (PIP) in this paper. The proposed control scheme consists of a fuzzy swing-up controller (FSC), a fuzzy sliding balance controller (FSBC), and a fuzzy compensation mechanism. The PIP with the designed FSC can upswing the pendulum quickly and have the controlled system be stable in the sense of approaching the desired system energy. The pendulum of PIP system can be stably balanced at the upright position with the presented FSBC, where the chattering effect is significantly eliminated. With the proposed compensation mechanism, the overaccumulated upswing energy can be effectively compensated such that the influence of disturbance can be overcome. The simulation results are included to indicate the effectiveness of the provided controller. Moreover, based on an embedded control kernel, an experimental setup for the PIP control system is built up. It shows that the real-time experiment results empirically support the promising performance of desire.

An Approximation of Interval Type-2 Fuzzy Controllers Using Fuzzy Ratio Switching Type-1 Fuzzy Controllers

In this paper, the interval type-2 fuzzy controllers (FCIT2s) are approximated using the fuzzy ratio switching type-1 FCs to avoid the complex type-reduction process required for the interval type-2 FCs. The fuzzy ratio switching type-1 FCs (FCFRST1s) are designed to be a fuzzy combination of the possible-leftmost and possible-rightmost type-1 FCs. The fuzzy ratio switching type-1 fuzzy control technique is applied with the sliding control technique to realize the hybrid fuzzy ratio switching type-1 fuzzy sliding controllers (HFSCFRST1s) for the double-pendulum-and-cart system. The simulation results and comparisons with other approaches are provided to demonstrate the effectiveness of the proposed HFSCFRST1s.

Fuzzy Formation Control and Collision Avoidance for Multiagent Systems

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.

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

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.