基于多目标遗传算法和多属性决策的船舶柴油机转速PID控制器参数优化

Multi-objective optimization and multi-attribute decision making for PID controller parameters tuning in ship diesel 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,采用改进非支配解排序的多目标遗传算法(NSGAII)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。给出了某型护卫舰主机转速PID控制的数值算例。计算结果表明,该联合方法通用性好,所设计的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 was presented for PID parameters based on multi-objective optimization technique. A hybrid approach was proposed. In the first stage, a fast non-dominating sorting genetic algo-rithm II （NSGA II） was employed to approximate the set of Pareto solution through an evolutionary optimization. In the subsequent stage, a multi-attribute decision making （MADM） approach was adopted to rank these solutions from best to worst in order to determine the best solution in a deterministic environment with a single decision maker. A PID design example for ship diesel was used to illustrate the analytical process. The ranking of Pareto solution is based on entropy weight and TOPSIS method.