面向人工肌肉驱动器的无模型自适应滑模控制研究

针对人工肌肉驱动器模型的控制策略较为复杂、控制参数较多、调节过程较为繁琐、通用性较差等问题.首先基于梯度法设计了无模型自适应滑模控制器(MFASMC)并对其稳定性进行了证明.然后,利用该控制器分别对离子交换聚合金属(IPMC)以及气动人工肌肉(PAM)两种典型人工肌肉驱动器进行控制仿真实验,从而对其控制精度、适应性及通用性进行验证.由仿真结果可知,通过设计控制器参数的调节规律,MFASMC算法可以实现对控制参数的快速在线调节,故对于不同种类的人工肌肉驱动器避免了繁杂的数学建模过程及控制参数调节过程,具有良好的适应性及通用性.

Study on Model Free Adaptive Sliding Mode Controller for Artificial Muscle Actuators

The traditional control strategies for artificial muscle actuators based on the control object model have drawbacks such as complex in control laws， too many control parameters which is tedious to adjust， and having poor universality. Thus， a model free adaptive sliding mode controller (MFASMC) was designed based on the gradient method and proved in stability. Then， the new algorithm was simulated to contorl the identification models of IPMC(ionic polymer metal composite) and PAM(pneumatic artifical muscle) respectively. The results proved that the control parameters can be adjusted online by the new MFASMC algorithm rapidly， by designing the control parameters regulation rules. In this way， MFASMC makes the modeling process is not necessary. Moreover， the good control effects can be obtained for various artificial muscle actuators with no need to adjust any control parameters. Therefore， MFASMC has good adaptability and universality.