摘要
为了使IPMC人工肌肉在仿生机器人中得到更好的应用,其期望的位置必须能够精确地控制.针对IPMC表现出的强非线性以及模型不确定性,首先采用滑模变结构对其进行控制,实现了在不确定因素下的系统鲁棒稳定,然后采用PI外环控制器对其进行跟踪,最后将神经网络应用到PI外环跟踪控制器的设计中.仿真结果表明,该系统不仅能够实现含有不确定性的IPMC人工肌肉精确位置跟踪,而且能在模型不确定性以及外部因素干扰下依旧保持稳定,鲁棒性能好.
To get better used for the IPMC in biomedical and robotic systems, the position that we expect must be controlled precisely. Against strong nonlinear properties and model uncertainties,as a result, an IPMC arti- ficial muscles position tracking control system based on sliding mode variable structure control and PI control approach is proposed. First, the robust stability is achieved by sliding mode control, furthermore, sliding mode variable structure control and PI control approach which are used to trace the position, finally, the pa- rameters of tracking controller are designed by using neural network. The designed system not only can achieve position tracking, but also guarantee stability in the presence of effect of uncertainties and external perturba- tion, the effectiveness of the proposed method is confirmed by simulation results.
出处
《郑州大学学报（工学版）》
CAS
北大核心
2014年第6期104-107,共4页
Journal of Zhengzhou University（Engineering Science）
基金
国家自然科学基金资助项目(61304115)
关键词
IPMC
不确定性
滑模变结构
神经网络
非线性位置控制
鲁棒稳定
IPMC
uncertainties
sliding mode variable structure
neural network
nonlinear position con-trol
robust stability
