Geuntaek Kang

Design of TSK fuzzy controller based on TSK fuzzy model using pole placement

This paper presents a Takagi-Sugeno-Kang (TSK) fuzzy controller based on a TSK fuzzy model consisting of TSK fuzzy rules of which consequents are a state equation and have a constant term. The proposed controller consists of TSK fuzzy rules and guarantees the stability of the closed loop system. The pole placement and the integral control developed for linear control systems are used for the TSK fuzzy controller. The behaviour of the closed loop system controlled by the suggested fuzzy controller is the same as the linear system of which state transition matrix is the desired one. This paper deals with both the continuous systems and the discrete systems.

Stability analysis of TSK fuzzy systems

This paper suggests a method verifying the stability of a Takagi-Sugeno-Kang (TSK) fuzzy state space model consisting of TSK fuzzy rules of which consequents have a constant term. Such a TSK fuzzy model may have many equilibrium points and each equilibrium point may have different nature of stability. The stability of an equilibrium point is determined by eigenvalues of the Jacobian matrix obtained by linearizing the system around the equilibrium point. This paper deals with both continuous systems and discrete systems.

A fuzzy model-based controller of an underwater robotic vehicle under the influence of thruster dynamics

Underwater robotic vehicles (URVs) have become an important tool for various underwater tasks because they have greater speed, endurance, depth capability, and safety than human divers. Many URVs powered by electric rotors driving propellers. The thruster system is known to be nonlinear and time-varying. The system dynamics of URVs can be greatly influenced by the thruster of dynamics at low speed or station keeping. Good control of a vehicle at low speed is also an important design problem which must be solved to permit important operations like automatic docking and combined vehicle-manipulator control. The conventional linear controller based on the simplified vehicle dynamics may not be able to handle these properties and result in poor performance. This paper describes a fuzzy model-based controller of an underwater robotic vehicle with the influence of the thruster dynamics. The fuzzy controller presented in this paper is based on a Tagaki-Sugeno-Kang (TSK) fuzzy model and guarantees the stability of overall fuzzy control system. Its superiority to the conventional linear controller is investigated by computer simulation.

A tactics for robot soccer with fuzzy logic mediator

This paper presents a tactics using fuzzy logic mediator that selects proper robot action depending on the positions and the roles of adjacent two robots. Conventional Q-learning algorithm, where the number of states increases exponentially with the number of robots, is not suitable for a robot soccer system, because it needs so much calculation that processing cannot be accomplished in real time. A modular Q-learning algorithm reduces a number of states by partitioning the concerned area, where mediator algorithm for cooperation of robots is used additionally. The proposed scheme not only reduces a number of a calculation but also combines a robot action selection with robot cooperation by means of fuzzy logic system.

Design of fuzzy state controllers and observers

This paper suggests methods for designing fuzzy state controllers and fuzzy state observers based on Takagi-Sukeno-Kang (TSK) fuzzy models (Takagi and Sukeno, 1985; Sukeno and Kang, 1988) which approximate complicated nonlinear systems to any degree of accuracy. First, a designing method of fuzzy state controllers, guaranteeing that the poles of the fuzzy control systems with fuzzy state controllers are to be desired ones, is suggested. Next, a designing method of fuzzy state observers, guaranteeing that the dynamics of state error vector have the desired poles, is suggested. Finally, fuzzy control systems with fuzzy state controllers and observers are constructed and it is showed that the so-called separation property of the observer-controller design procedure is satisfied.<<ETX>>

Transformation of TSK fuzzy system into fuzzy system with singleton consequents and its application

A TSK fuzzy system can represent the behavior of a complex nonlinear system with a low number of rules with the desired accuracy and guarantee the stability of the closed loop system, while the interpretation of the rules is difficult due to the functional nature of the consequents. On the contrary, the fuzzy controller with singleton consequents is understandable intuitively and adjustable easily due to linguistic expression of the rules. The paper suggests a method transforming TSK fuzzy systems into fuzzy systems with singleton consequents, and shows its application designing a fuzzy controller with singleton consequents by using the TSK fuzzy system when the behavior of a nonlinear system is described with a singleton fuzzy model by a human expert.

Navigation of an Autonomous Mobile Robot with Vision and IR Sensors Using Fuzzy Rules

Algorithms of path planning and obstacle avoidance are essential to autonomous mobile robots that are working in unknown environments in the real time. This paper presents a new navigation algorithm for an autonomous mobile robot with vision and IR sensors using fuzzy rules. Temporary targets are set up by distance variation method and then the algorithms of trajectory planning and obstacle avoidance are designed using fuzzy rules. In this approach, several digital image processing technique is employed to detect edge of obstacles and the distances between the mobile robot and the obstacles are measured. An autonomous mobile robot with single vision and IR sensors is built up for experiments. We also show that the autonomous mobile robot with the proposed algorithm is navigating very well in complex unknown environments.

Adaptive Fuzzy Control of Helicopter

This paper presents an adaptive fuzzy control scheme for nonlinear helicopter system which has uncertainty or unknown variations in parameters. The proposed adaptive fuzzy controller is a model reference adaptive controller. The parameters of fuzzy controller are adjusted so that the plant output tracks the reference model output. It is shown that the adaptive law guarantees the stability of the closed-loop system by using Lyapunov function. Several experiments with a small model helicopter having parameter variations are performed to show the usefulness of the proposed adaptive fuzzy controller.

Adaptive PID Controller for Nonlinear Systems using Fuzzy Model

This paper presents an adaptive PID control scheme for nonlinear system. TSK(Takagi-Sugeno-Kang) fuzzy model is used to estimate the error of control input, and the parameters of PID controller are adapted using the error. The parameters of TSK fuzzy model also adapted to plant. The proposed algorithm allows designing adaptive PID controller which Is adapted to the uncertainty of nonlinear plant and the change of parameters. The usefulness of the proposed algorithm is also certificated by the several simulations.

Temperature control of the Rework-system using fuzzy PID controller

Rework systems are the equipment used to install or remove semiconductor chips with BGA or SMD forms in printed circuit boards. The rework systems have hot air outlets. At the outlets, precise temperature control is needed to avoid heat shock. The aim of this paper was to suggest a new controller for temperature control at the hot air outlets. The suggested controller was a fuzzy PID controller. The fuzzy PID controllers were composed of TSK fuzzy rules and had outstanding ability for nonlinear systems control. This paper reports the design algorithm of fuzzy PID controllers, and the design process of the fuzzy PID controller for the temperature control of the outlets. Temperature control experiments were performed to verify the ability of the suggested controller. As a result, the RMS of the proposed method is 9.44 and the general method is 15.88. The experiments showed that the temperatures at the outlet using the suggested fuzzy PID controller followed the desired ones better than the commonly used PID controller.