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EN
This paper presents a feasible design for a con- trol algorithm to synthesize an adaptive neuro-fuzzy inference system-based PID continuous sliding mode control system (ANFIS- PIDCSMC) for adaptive trajectory tracking control of the rigid robot manipulators (RRMs) in the joint space. First, a PID sliding mode control algorithm with sliding surface dynamics-based continuous proportional-integral (PI) control action (PIDSMC-SSDCPI) is presented. The global stability conditions are formulated in terms of Lyapunov full quadratic form such that the robot system output can track the desired reference output. Second, to increase the control system robustness, the PI control action in the PIDSMC- SSDCPI controller is supplanted by an ANFIS control signal to provide a control approach that can be termed adaptive neuro-fuzzy inference system-based PID continuous sliding mode control system (ANFIS-PIDCSMC). For the proposed control algorithm, numerical simulations using the dynamic model of RRM with uncertainties and external disturbances show high quality and effectiveness of the adopted control approach in high-speed trajectory tracking control problems. The simulation results that are compared with the results, obtained for the traditional controllers (standalone PID and traditional sliding mode controller (TSMC)), illustrate the fact that the tracking control behavior of the robot system achieves acceptable tracking performance.
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