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Novel Approach to Nonlinear PID Parameter Optimization Using Ant Colony Optimization Algorithm 被引量:11

Novel Approach to Nonlinear PID Parameter Optimization Using Ant Colony Optimization Algorithm
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摘要 This paper presents an application of an Ant Colony Optimization (ACO) algorithm to optimize the parameters in the design of a type of nonlinear PID controller. The ACO algorithm is a novel heuristic bionic algorithm, which is based on the behaviour of real ants in nature searching for food. In order to optimize the parameters of the nonlinear PID controller using ACO algorithm, an objective function based on position tracing error was constructed, and elitist strategy was adopted in the improved ACO algorithm. Detailed simulation steps are presented. This nonlinear PID controller using the ACO algorithm has high precision of control and quick response. This paper presents an application of an Ant Colony Optimization (ACO) algorithm to optimize the parameters in the design of a type of nonlinear PID controller. The ACO algorithm is a novel heuristic bionic algorithm, which is based on the behaviour of real ants in nature searching for food. In order to optimize the parameters of the nonlinear PID controller using ACO algorithm, an objective function based on position tracing error was constructed, and elitist strategy was adopted in the improved ACO algorithm. Detailed simulation steps are presented. This nonlinear PID controller using the ACO algorithm has high precision of control and quick response.
出处 《Journal of Bionic Engineering》 SCIE EI CSCD 2006年第2期73-78,共6页 仿生工程学报(英文版)
关键词 Ant Colony Optimization ALGORITHM PHEROMONE nonlinear PID parameter optimization Ant Colony Optimization, algorithm, pheromone, nonlinear PID, parameter optimization
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