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 algorith...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.展开更多
A novel distributed control scheme to generate stable flocking motion for a group of agents is proposed.In this control scheme,a molecular potential field model is applied as the potential field function because of it...A novel distributed control scheme to generate stable flocking motion for a group of agents is proposed.In this control scheme,a molecular potential field model is applied as the potential field function because of its smoothness and unique shape.The approach of distributed receding horizon control is adopted to drive each agent to find its optimal control input to lower its potential at every step.Experimental results show that this proposed control scheme can ensure that all agents eventually converge to a stable flocking formation with a common velocity and the collisions can also be avoided at the same time.展开更多
文摘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.
基金Supported by the National Natural Science Foundation of China under Grant Nos 60975072 and 60604009the Program for New Century Excellent Talents in University of China under Grant No NCET-10-0021+1 种基金the Fundamental Research Funds for the Central Universities under Grant No YWF-10-01-A18Open Fund of the State Key Laboratory of Virtual Reality Technology and Systems and Beijing NOVA Program Foundation under Grant No 2007A017.
文摘A novel distributed control scheme to generate stable flocking motion for a group of agents is proposed.In this control scheme,a molecular potential field model is applied as the potential field function because of its smoothness and unique shape.The approach of distributed receding horizon control is adopted to drive each agent to find its optimal control input to lower its potential at every step.Experimental results show that this proposed control scheme can ensure that all agents eventually converge to a stable flocking formation with a common velocity and the collisions can also be avoided at the same time.
