Intelligent PID Control Systems Discussions

• Main Authors: Yan-Wen Huang, 黃燕文
• Other Authors: 董必正
• Format: Others
• Language: en_US
• Published: 2007
• Online Access: http://ndltd.ncl.edu.tw/handle/24786452012529906136

博士 === 國立中央大學 === 機械工程研究所 === 95 === Fixed-gain PID (Proportional-Integral-Derivate) controller is the most commonly used controller in the industry. However, it is obviously not able to fulfill the needs of a system with gain uncertainty and nonlinearity. In order to contain the case of complex objectives applied on the system, such as the external noises and the uncertain parameters of system, an adjustable gain controller is necessary for the system robustness requirement. This thesis aims on the study of intelligent PID controller with adjustable gains applied on different cases of nonlinear system. Intelligence defines as “the capacity to acquire and apply knowledge.” The use of such a broad definition could imply that the simplest microprocessor implementing a Proportional-Integral-Derivate (PID) controller is, in fact, intelligent because it continuously acquires knowledge (plant output data, reference inputs, the error relationship between them, etc.) and applies it (by generating control inputs to the plant). Intelligent control methodologies include the use of (biologically motivated) genetic algorithms to solve control problem (see, e.g., the work for the use of genetic algorithms for adaptive control). Genetic algorithms do not have much mathematical requirements about the optimization problem. Other intelligent control methodologies include the fuzzy control methodology. Firstly, a based on genetic algorithms (GA’s) tuning method for PID controller parameters control design is presented using shield metal arc welding (SMAW) process. Due to a large number of computer operations must carry out on GAs computing; computer system simulation on was performed to search for the optimum controller parameters. After simulation, the parameters were then brought into the actual system to carry out the welding tasks. However, because of the continuous changing of welding rod length and electric arc length, the simulated controller parameters are not fully satisfied to the changing of welding condition. Consequently the experiment showed a not so uniform welding quality which was caused by the fixed controller gain applied on the system. This part of study was arranged on the appendix A. Secondly, actuator saturation exists in almost every real control system and may give rise to the windup phenomenon. The term “windup” stems from the tendency of integral controllers to “wind up” during input saturation. If input saturation is active, the open loop dynamics become effective; these can give rise to enormous controller output signal during saturation, causing big overshoots and often badly decaying transients. Since these undesired effects of plant input saturation can be attributed to the controller, they are called “controller windup”. But also after controller windup prevention, the loop remains nonlinear, and input saturation can have a destabilize effect. If the closed loop dynamics assigned by this control are “too fast”, nonlinear overshoots, limit cycles or closed loop instability can occur. Since this problem is not related to the compensator but to the compensator but to the controlled plant dynamics, it is called “plant windup”. This effect is caused by inappropriate plant states, and is therefore referred to as “plant windup”. However, this “windup phenomenon” leads to degradation in the performance of controlled systems and results in large overshoots, long settling times, severe transient oscillations, and system instability. Therefore, when the controlled process is nonlinear, a fixed gain PID controller cannot usually give satisfactory control performance at some operating points, since the controller parameters must be adjusted following a change in operating condition. Hence, some anti-windup schemes are proposed for the stabilizing nominal control system, which with sector nonlinearity input saturation. This linear transfer function has no effect when the actuators are operating linearly, but modifies the system’s behavior during and following a saturation event to ensure stability and eventual escape from saturation, and so that the intended linear behavior is restored reasonable quickly after saturation has occurred.