An Intelligent Cooperative Game Approach for Adaptive Robust Control of Fuzzy Mechanical Systems

Since the actual environment of mechanical systems is not ideal, there will be some unstable factors, namely uncertainty. Such uncertainty is changeable and bounded, but its boundary is usually uncertain. To describe the uncertain boundary, the fuzzy set theory is used in this article, which is one of the innovations of this article. On this basis, an adaptive robust control method based on two control parameters is proposed, which is for the fuzzy mechanical systems. It is proved by Lyapunov function that this control approach can ensure the global uniform boundedness and global uniform ultimate boundedness performance of the controlled mechanical system. This is the first level of the control design. Afterward, the second level is to ensure the control performance while reducing the control cost by optimizing two control parameters. In order to optimize two control parameters, the cooperative game theory is adopted, which is another one of the innovations of this article. In the optimization process, two control parameters are regarded as two players, and the optimal control parameters are obtained by minimizing the cost function designed based on these two players. Finally, a serial robot model is adopted to verify the feasibility and superiority of the proposed control approach.