Abstract
According to the robot’s dynamics, a high performance algorithm based on dynamic surface control is introduced to track desired trajectory, and simulations are conducted on a selective compliance assembly robot arm-type manipulator to verify the algorithm. The traditional dynamic surface control is designed based on dynamic model, which requires exact model information. Due to the model uncertainty and complex environments, the tracking performance of the controller can be significantly decreased. Therefore, a model-free fuzzy adaptive dynamic surface controller is designed, by adopting a fuzzy system with Lyapunov self-adaptation law. The new controller efficiently improves the dynamic quality. The simulation results prove that the designed model-free controller ensures that all the states and signals of the closed-loop system are bounded, the system has a faster response speed and smaller steady-state error comparing with the traditional dynamic surface control using the selective compliance assembly robot arm model, and the tracking error converge to a very small scale. Besides, the proposed algorithm can track the desired trajectory with high performance without the prior knowledge of specific parameters from the experimental manipulator, which simplifies the complexity of building the control system.
Highlights
Robot trajectory tracking has wide applications in robotic systems
Given the track profile function, Abad et al.[4] designed an optimal navigation algorithm for unmanned ground vehicle; Coelho and Nunes[5] implemented a Kalman-based active observer controller under nonholonomic constraints on wheeled mobile robots, to improve the robustness of the path following; and Matveev et al.[6] proposed a sliding mode strategy which can be used for the navigation of a unicycle-like robot under moving obstacles
Since the first selective compliance assembly robot arm (SCARA) was designed by Hiroshi Makino in 1978, this kind of four-degree robot is widely used in industries, high-speed and precision of motion.[7]
Summary
Robot trajectory tracking has wide applications in robotic systems. Robotic motion control problems with constraints require novel control laws to improve the performance.[1,2,3] Given the track profile function, Abad et al.[4] designed an optimal navigation algorithm for unmanned ground vehicle; Coelho and Nunes[5] implemented a Kalman-based active observer controller under nonholonomic constraints on wheeled mobile robots, to improve the robustness of the path following; and Matveev et al.[6] proposed a sliding mode strategy which can be used for the navigation of a unicycle-like robot under moving obstacles. To realize a control law without model parameters and improve the tracking speed, DSC algorithm combined with adaptive controller and fuzzy state observer is proposed in paper.[20,21,22] many research studies lack the industrial scene application. The proposed DSC algorithm which achieves a whole closed-loop system satisfies the desired dynamic and static performance and guarantees a high performance tracking trajectory.[23] Fuzzy logic systems are used to approach the uncertain model functions of the control target.[24] The proposed algorithm guarantees the uniform boundedness of all the signals in the closed-loop system. SCARA-type robots are characterized by its small load and fast speed They are mainly used in such applications as fast sorting, precision assembly in computing, communication, and consumer (3C) industry, food industry, and so on.
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