1. Introduction
Over the past half-century, a large number of robots have been designed and manufactured [1]. The development of robot control theory has made great progress, such as PID control, sliding mode control, adaptive control, fuzzy control, neural network control, etc. [2-6]. The dynamic model of industrial robots has nonlinearity and various uncertainties, such as friction, external disturbances and load changes. When the physical model of the control system is uncertain, it is difficult to obtain good performance. Therefore, how to design a robot controller is a serious challenge.
In recent decades, sliding mode control has received considerable attention because it involves designing a suitable state-space surface, called the sliding surface, and using a high-speed switching control law to make the state-space trajectory of the nonlinear system asymptotically reach the sliding surface and remain on it for a period of time. Sliding mode control is a robust control method for controlling nonlinear systems under uncertain conditions of the control system model. Therefore, it has good robustness to system model uncertainties and external disturbances [7-9]. The main characteristics of sliding mode control are as follows: (1) fast response and good transient performance; (2) robustness to most disturbances or model uncertainties; (3) providing possibilities for some complex nonlinear systems that are difficult to stabilize using continuous state feedback methods. However, due to the discontinuity of the control law in sliding mode control, the system will inevitably experience "chattering," which will have adverse effects on the system. Using the boundary layer method can eliminate or mitigate the chattering phenomenon, but it is necessary to weigh the relationship between system performance and chattering.
This paper proposes an adaptive controller to address the chattering problem. Regarding system uncertainties, the controller employs a strategy combining sliding mode variable structure and adaptive control. Based on sliding mode control, an adaptive algorithm is added to continuously improve system chattering by timely identifying, learning, and adjusting the control law. This method will be proven to converge the tracking error to zero. Simulation results will verify whether the proposed control strategy can effectively and efficiently perform trajectory tracking control.
2. Problem Description
6. Conclusion
This paper proposes a simple and effective adaptive sliding mode composite control strategy. Its stability is verified using Lyapunov's theorem, ensuring robustness and tracking performance. The designed adaptive law can identify system parameters online in a timely manner, effectively mitigating control input jitter. Theoretical analysis and system simulation demonstrate that this control strategy can guarantee global stability and achieve good tracking results.
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