摘要
建立冗余直接驱动式电液伺服系统的数学模型。针对电液伺服系统时变、强非线性的特点以及冗余伺服系统在余度降级过程中的故障瞬态现象和余度降级后的性能降级现象,考虑传统PID控制器自适应能力不强、鲁棒性差等缺陷,提出神经网络自适应控制方案。根据冗余电液伺服系统的特点和目前神经网络控制的发展水平,采用基于径向基函数神经网络的智能PID控制器实现冗余伺服系统的自适应控制。研究结果表明:该控制器能够根据控制指令、被控对象结构参数等因素的变化实时调整控制器参数,和传统PID控制器相比具有控制精度高、鲁棒性强的特点,可以有效地克服冗余伺服系统余度切换时的故障瞬态现象和余度降级后的性能降低现象。
A mathematical model of redundant direct drive electro-hydraulic servo system is built up. However it is not easy to control such a system precisely for it is time-variant and non-linear, besides that there is an unsteady transitional state during switching between different redundancies and characteristic of the servo system deteriorates with the degrading of the redundancies. Considering these factors, an adaptive control algorithm based on neural networks （NN） is introduced to improve the traditional algorithm which has such disadvantages as poor self-adaptability and poor robustness. According to characteristics of the servo system and the development of the neural network nowadays, a RBF neural network based PID controller is adopted in the controlling of the redundant actuator to solve the above problems. Results of the simulation show that the controller adjusts controlling parameters according to the instructions and structure of the controlled object. It is of high precision and strongly adaptive and it solves the problems brought by redundancy technology.
出处
《机械工程学报》
EI
CAS
CSCD
北大核心
2008年第12期249-253,共5页
Journal of Mechanical Engineering
基金
国家航空基金资助项目(04E51013)
关键词
冗余
伺服控制
神经网络
自适应控制
Redundancy Servo control Artificial neural network Adaptive control
