In this paper, fuzzy logic is used to perform switching controllers for Multiple Model Adaptive Control (MMAC) in manipulator robot. In the cases which uncertainty bounds of system’s parameters are large, the performance and stability issue of system are considerable concerns. Multiple Model Adaptive Control approach can be useful method to stabilize these kinds of systems. In this control method, the uncertainty bound is divided into several smaller bounds. As a result, the process of stabilization would be streamlined. In this regard, one estimation is obtained for uncertain parameter in every minor bound, and based on estimation errors designed controller can alter. In order to avoid switching controllers and pertinent challenges a summation of controllers with coefficient tuned by fuzzy logic is considered. Simulation results substantiate the efficacy of this method.
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In this paper a control algorithm based on a design technique named "Robust Damping Control" is introduced. A robust observer is further shown to overcome the problem of using velocity sensors that may degrade the system performance. The proposed controller uses only position measurements and is capable of disturbance rejection in the presence of unknown bounded disturbances without requiring the knowledge of its bound. Moreover, we propose an accurate and fast time integration method to solve the dynamic equations of the mobile manipulator system. The simulation results of a 6 D.O.F. mobile manipulator illustrate the effectiveness of the presented algorithm.
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