Optimal PID Controller Design for AVR System

99學年度翁慶昌研究獎補助論文[[abstract]]In this paper, a real-valued genetic algorithm (RGA) and a particle swarm optimization (PSO) algorithm with a new fitness function method are proposed to design a PID controller for the Automatic Voltage Regulator (AVR) system. The proposed fitness function can let the RGA and PSO algorithm search a high-quality solution effectively and improve the transient response of the controlled system. The proposed algorithms are applied in the PID controller design for the AVR system. Some simulation and comparison results are presented.We can see that the proposed RGA and PSO algorithm with this new fitness function can find a PID control parameter set effectively so that the controlled AVR system has a better control performance.[[notice]]補正完畢[[incitationindex]]EI[[booktype]]紙

Realization of linear defuzzified output via mixed fuzzy logics

The realization of a linear defuzzified output of a fuzzy controller by appropriate choice of each component of the fuzzy controller is discussed. The fuzzy controller with a simplified fuzzy reasoning method is described. The linear defuzzified output of the fuzzy controller is discussed, where arbitrary numbers of triangular fuzzy numbers are employed to fuzzify the linguistic variables in fuzzy control rules. Using three mixed fuzzy logics, the author shows that the defuzzified output can be precisely equivalent to a linear function of all the inputs to the fuzzy controller[[abstract]]The realization of a linear defuzzified output of a fuzzy controller by appropriate choice of each component of the fuzzy controller is discussed. The fuzzy controller with a simplified fuzzy reasoning method is described. The linear defuzzified output of the fuzzy controller is discussed, where arbitrary numbers of triangular fuzzy numbers are employed to fuzzify the linguistic variables in fuzzy control rules. Using three mixed fuzzy logics, the author shows that the defuzzified output can be precisely equivalent to a linear function of all the inputs to the fuzzy controller[[conferencetype]]國際[[conferencedate]]19930328~19930401[[booktype]]紙本[[conferencelocation]]San Francisco, United State

Remote controlled game platform by USB joysticks

[[abstract]]In this paper, a designed and implemented method of a robot soccer game platform is proposed. This platform includes three main parts: (a) four joysticks and each with an USB connector, (b) a transmission electric board with four USB connection ports, and (c) four omni-directional mobile robots with three-wheel mechanism. Players can control the omni-directional robot to play a soccer game by using USB joysticks through the wireless communication.[[conferencetype]]國際[[conferencelocation]]Taipei, Taiwa

Omnidirectional Vision-based Robot Localization on Soccer Field by Particle Filter

[[abstract]]An omnidirectional vision-based localization method based on the particle Alter is proposed to achieve the location of robot on a soccer field in this paper. Two kinds of sensor information are considered in the method to let the robot on the soccer field can estimate its location and then to decide an appropriate strategy. One is the robot action sensor information obtained by the motor's feedback and the other is the observation sensor information obtained by the image captured by an omnidirectional vision system. The action sensor information is used to expect the robot location distribution. The location distribution is represented by particles. The omnidirectional image is used to observe the environment information. The differences between these particles location's environment information and the robot observation environment information are considered to calculate the belief values of particles. Then the posture of the particle with the highest belief is used to be the estimated posture of the robot. Some experimental results are presented to illustrate the effectiveness of the proposed method.[[conferencetype]]國際[[conferencedate]]20100818~20100821[[iscallforpapers]]Y[[conferencelocation]]Taipei, Taiwa

Design of fuzzy control systems with a switching grey prediction

[[abstract]]A switching grey prediction fuzzy control system structure is proposed in this paper. In the design of the switching grey predictor, we divide the system response into some regions and propose a switching mechanism so that different forecasting step-size is given in the different region to simultaneously improve the transient and steady state responses of the controlled system. Moreover, we apply simulated annealing to find the appropriate parameter values so that the controlled system has a high control performance. Finally, simulation results of the inverted pendulum system are provided to prove the efficiency of the proposed methods[[conferencetype]]國際[[conferencedate]]19980504~19980509[[conferencedate]]Anchorage, AK, USA[[iscallforpapers]]

Design of fuzzy classification system using genetic algorithms

[[abstract]]This paper proposes a GA-based method to construct an appropriate fuzzy classification system to maximize the number of correctly classified patterns and minimize the number of fuzzy rules. In this method, a fuzzy classification system is coded as an individual in the GA. A fitness function is defined such that it can guide the search procedure to select an appropriate fuzzy classification system to maximize the number of correctly classified patterns and minimize the number of fuzzy rules. Finally, a two-class classification problem is utilized to illustrate the efficiency of the proposed method[[conferencetype]]國際[[conferencedate]]20000507~20000510[[iscallforpapers]]Y[[conferencelocation]]San Antonio, TX, US