Hai-Won Yang

A generalized Chua-type vector hysteresis model for both the non-oriented and grain-oriented electrical steel sheets

This paper presents a generalized Chua-type vector hysteresis model to describe the scalar and vector properties of silicon steel sheets. The proposed model can be applied to both Non-oriented and Grain-oriented silicon steel sheets under arbitrary alternating, rotating, mixed and distorted magnetic flux density conditions considering the eddy current effects.

An indirect adaptive fuzzy sliding-mode control for decoupled nonlinear systems

In this paper, a decoupled fuzzy sliding-mode control design scheme is presented through width adaptation for a class of fourth-order nonlinear systems. Each subsystem, which is decoupled into two second-order systems, is said to have main and sub control purpose. Two sliding surfaces are constructed through the state variables of the decoupled subsystem. We define main and sub target condition for these sliding surfaces, and introduce an intermediate variable from the sub sliding surface condition. The proposed adaptation law, which results from the indirect adaptive approach, is used to appropriately determine the width of the unknown system variables. And the membership functions in the THEN part will vary with the width adaptation. An adaptive law is then used to tune the width in the THEN part to appropriately determine the distribution of each membership function. The main advantage of the proposed method is that the structure of fuzzy controller dose not need to be changed while using a common design procedure and the computing time may be reduced considerably. Finally, a nonlinear system simulation example is shown to verify the effectiveness of the proposed adaptive fuzzy-sliding mode controller.

The PSO-PID Speed Controller Design for the BLDC Motor

Brushless DC motors applied in many control systems because of the good respose characteristic and the easy control characteristic. The speed control of the BLDC motors is important in the systems. This paper has designed PSO-PID speed controller for the speed control of BLDC motors. The PSO algorithm optimized the parameters of the PID controller in the PSO-PID speed controller. The several methods obtained the optimal inertia weight of the PSO algorithm by comparison. The optimal inertia weight of the PSO algorithm optimized the PSO-PID speed controller for BLDC motors. This paper confirmed the performance of proposed PSO-PID speed controller through simulation results.

Decoupled adaptive fuzzy sliding-mode control

We propose a decoupled adaptive fuzzy sliding-mode control scheme for a class of fourth-order nonlinear systems. The system is decoupled into two second-order systems, where each subsystem has a separate control purpose expressed in terms of a sliding surface. Then, using the information from the secondary target conditions, the main target generates a control action to make both subsystems move toward their sliding surfaces, respectively. Two sets of fuzzy rule bases are utilized to represent the equivalent control input with unknown system functions of the main target. The membership functions of the THEN-part, which is used to construct a suitable equivalent control of SMC (sliding mode control), are changed according to the adaptive law.

An implementation of a rotational inverted pendulum using adaptive fuzzy controllers

In this paper, three controllers are considered for a rotational inverted pendulum system (RIPS). The control objectives are to position the pendulum at the upright position and to regulate it at the specified position. The fuzzy control is an effective way to achieve the control objectives in a nonlinear system such as the RIPS. PID controller, fuzzy PID controller and adaptive fuzzy controller are proposed to obtain increased control performance and stability. This paper consists of three parts: (1) modeling of the RIPS, (2) introduction of three control methods for the control of the system, and (3) making a prototype of the system and experimental environment to compare the performances of three controllers.

A design of a hybrid control system using neural networks

This paper deals with a design of hybrid control system with an advanced PD controller and a neuro-controller in parallel. An advanced PD controller is designed to tune the parameters of the PD controller with a fuzzy controller properly. And neuro-controller with a memory neuron is used to control complex dynamical systems effectively. Simulations on the two link robot manipulator prove the effectiveness of the hybrid control system.

Implementation of stable adaptive neural networks for feedback linearization

For a class of single-input single-output continuous-time nonlinear systems, a multilayer neural network-based controller that feedback linearizes the system is presented. Control action is used to achieve tracking performance for a state feedback linearizable but unknown nonlinear system. We show that indirect adaptive schemes will learn how to control the plant, result in bounded internal signals, and achieve stable tracking for a reference input asymptotically. The multilayer neural network (NN) is used to approximate given plant to any desired degree of accuracy and generate the feedback control. Based on the error between the plant output and the desired output, the weight-update rule of NN is derived to satisfy Lyapunov stability. A projection method is employed so that NN weights are bounded. It is shown that all the signals in the closed-loop system are uniformly bounded under mild assumptions. The initialization of NN weights is straightforward. The performance of an indirect adaptive scheme is demonstrated through the control of an inverted pendulum system and a system with internal dynamics.