基于多目标遗传算法和多属性决策的船舶PID控制器参数整定

Multi-objective optimization and multi-attribute decision making for PID controller parameters tuning in ship design

提出了一种基于多目标遗传算法和多属性决策的PID参数设计方法,综合考虑系统超调量、稳定时间和ITAE指标,采用多目标遗传算法(MOGA)求出Pareto最优解。由这些Pareto最优解构成决策矩阵,使用客观赋权的信息熵法对最优解的属性进行权值计算,然后采用逼近理想解的排序方法(TOPSIS)进行多属性决策(MADM)研究,对Pareto最优解给出排序。计算了一个二阶船舶控制的数值算例,结果表明本文提出的联合方法通用性好,设计的PID性能优异,适合工程实际应用。

The tuning of PID controller parameters is the most important task in PID design process. A new tuning method is present for PID parameters based on muhiobjective optimization technique. A hybrid approaches is proposed. In the first stage, a Muhiobjective Optimization Genetic Algorithm II （MOGA） is employed to approximate the set of Pareto solution through an evolutionary optimization process. In the subsequent stage, a multi-attribute decision making （MADM）approach is adopted to rank these solutions from best to worst and to determine the best solution in a deterministic environment with a single decision maker. A PID design example for a ship is conducted to illustrate the analysis process in present study. The ranking of Pareto solution is based on entropy weight and TOPSIS method.