Due to the difficulty of controlling the process with inverse response and dead time,a Multi-objective Optimization based on Genetic Algorithm (MOGA) method for tuning of proportional-integral-derivative (PID) control...Due to the difficulty of controlling the process with inverse response and dead time,a Multi-objective Optimization based on Genetic Algorithm (MOGA) method for tuning of proportional-integral-derivative (PID) controller is proposed. The settings of the controller are valued by two criteria,the error between output and reference signals and control moves. An appropriate set of Pareto optimal setting of the PID controller is founded by analyzing the results of Pareto optimal surfaces for balancing the two criteria. A high order process with inverse response and dead time is used to illustrate the results of the proposed method. And the efficiency and robustness of the tuning method are evident compared with methods in recent literature.展开更多
基金National Natural Science Foundation of China (No.60504033)
文摘Due to the difficulty of controlling the process with inverse response and dead time,a Multi-objective Optimization based on Genetic Algorithm (MOGA) method for tuning of proportional-integral-derivative (PID) controller is proposed. The settings of the controller are valued by two criteria,the error between output and reference signals and control moves. An appropriate set of Pareto optimal setting of the PID controller is founded by analyzing the results of Pareto optimal surfaces for balancing the two criteria. A high order process with inverse response and dead time is used to illustrate the results of the proposed method. And the efficiency and robustness of the tuning method are evident compared with methods in recent literature.
