This paper proposes a fuzzy TSK controller to control a rotary flexible joint manipulator. The flexibility of joint is performed by means of a solenoid nonlinear spring, which is connected between actuator output and joint input in a bilateral connection form to transfer the produced torque; also the smooth model of frictions is used for modeling the dynamics of flexible manipulator. The effect of coulomb friction and also gearbox backlashes is decreased by a pulsation signal as an extra voltage that is added to the control voltage of actuator. Actuator dynamics is modeled by consideration of saturation mode of armature current. Experimental results demonstrate that the proposed controller has an ability to control flexible joint manipulator with a good performance.
The main purpose of the paper is to optimize state feedback parameters using intelligent method, GA, Hermite-Biehler, and chaos algorithm. GA is implemented for local search but it has some deficiencies such as trapping into a local minimum and slow convergence, so the combination of Hermite-Biehler and chaos algorithm has been added to GA to avoid its deficiencies. Dividing search space is usually done by distributed population genetic algorithm (DPGA). Moreover, using generalized Hermite-Biehler Theorem can find the domain of parameters. In order to speed up the convergence at the first step, Hermite-Biehler method finds some intervals for controller, in the next step the GA will be added, and, finally, chaos disturbance will help the algorithm to reach a global minimum. Therefore, the proposed method can optimize the parameters of the state feedback controller.
This paper introduces a new approach to design Model-Free Adaptive Controller (MFAC) using adaptive fuzzy procedure as a feedback linearization based on output error. The basic idea is to transfer the control signal to an appropriate surface and then, depending on the output error of system, the control signal changes around this surface. Some examples are provided as well to illustrate the efficiency of the proposed approach. The obtained simulation results have shown good performances of the proposed controller.
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