摘要
针对自主式小车作业过程会受到环境的影响且控制系统具有未知性、多变量、随机性和非线性的特点,将模糊控制器和模糊神经网络相结合构成双环串级的闭环形式,利用一种改进的变尺度混沌优化算法对两个控制器参数进行整定,以实现复杂系统的优化控制。该算法简单,不依赖对象的精确数学模型,避免了设计过程中大量的参数调试工作。仿真和实验结果表明:系统具有响应速度快,超调量小、跟踪性能好的特点。
Aiming at the characteristic of autonomous vehicle such as the effect of environment during working process, the control system with unknown and multvariable and random and nonlinear, the closed loop of double loops in series by fuzzy controller and fuzzy neural network controller component was proposed. An improved mutative scale chaotic optimization algorithm was used for tuning parameters of two controllers so as to realize the optimal control of complex system. The method is simple and independent on the accurate mathematic model of the plant and avoids a mass work of tuning of parameters on design process, Simulation and experiment results show that the system has advantages such as fast response, small overshoot and good tracking character.
出处
《系统仿真学报》
CAS
CSCD
北大核心
2009年第22期7118-7120,7126,共4页
Journal of System Simulation
基金
国家863计划项目(2006AA10Z262)
华南农业大学校长基金(K071700
2008X004)
关键词
自主式
小车
模糊控制器
混沌优化
autonomous
vehicle
fuzzy controller
chaotic optimization