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:智能算法如粒子群算法已被应用于PID控制器的参数优化,以弥补传统优化方法容易产生振荡和较大超调量
的不足,但是粒子群算法存在易于早熟的缺点,在分析量子粒子群算法的基础上,提出了使用量子粒子群算法优化PID控
制器的参数。为了兼顾控制系统的各项性能指标,根据控制器的实际要求对各项指标进行加权作为算法的目标函数,对
PID控制器进行多目标寻优。通过2个传递函数实例,分别使用z—N、粒子群算法和量子粒子群算法进行了PID控制器
参数优化设计,并对结果进行了分析。-Abstract:Heuristics such as particle swarnl optimization is employed to enhance the capability of traditional techniques,
which is easy to produce surge and big overshoot,but PS0 may be trapped in the local optima of the objective and lead to poor performance.
This paper propesed the quantum-behaved particle 8wsl in optimization for the parameter optimization of PID controller.
A fitness function containing performance indexes Was defined and the algorithm Was used in multi-object optimization of PID controllers.
Two examples were given to illustrate the design procedure and exhibit the effectiveness of the proposed method via tomo
parison study with the existing Z—N and PSO approaches.
的不足,但是粒子群算法存在易于早熟的缺点,在分析量子粒子群算法的基础上,提出了使用量子粒子群算法优化PID控
制器的参数。为了兼顾控制系统的各项性能指标,根据控制器的实际要求对各项指标进行加权作为算法的目标函数,对
PID控制器进行多目标寻优。通过2个传递函数实例,分别使用z—N、粒子群算法和量子粒子群算法进行了PID控制器
参数优化设计,并对结果进行了分析。-Abstract:Heuristics such as particle swarnl optimization is employed to enhance the capability of traditional techniques,
which is easy to produce surge and big overshoot,but PS0 may be trapped in the local optima of the objective and lead to poor performance.
This paper propesed the quantum-behaved particle 8wsl in optimization for the parameter optimization of PID controller.
A fitness function containing performance indexes Was defined and the algorithm Was used in multi-object optimization of PID controllers.
Two examples were given to illustrate the design procedure and exhibit the effectiveness of the proposed method via tomo
parison study with the existing Z—N and PSO approaches.
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2、PID控制器的量子粒子群多目标优化设计.pdf