Control Strategy for Stability Improvement of Multi-Degree-of-Freedom Mechanical Manipulation Platforms

Abstract To address the issues of nonlinear coupling, dynamic uncertainty, and external disturbances existing in multi-degree-of-freedom (multi-DOF) mechanical operation platforms, this study proposes a stability improvement strategy based on improved Sliding Mode Control (SMC) and Particle Swarm Optimization (PSO) parameter tuning. By establishing the platform's dynamic model and designing an improved SMC law, a continuous approximation function and a coupling torque compensation term are introduced to reduce chattering and overshoot. Meanwhile, PSO is used to conduct a global search for sliding mode gains and sliding surface parameters, realizing the adaptive optimization of controller parameters. In simulations and actual experiments, the average response time, overshoot, and oscillation amplitude of the proposed strategy under different working conditions are 1.06 s, 3.7%, and 0.010, respectively. All these indicators are better than those of the traditional Proportional-Integral-Derivative (PID) controller (1.44 s, 9.2%, 0.031) and the conventional SMC (1.20 s, 6.0%, 0.018). This indicates that the platform can achieve fast convergence and stable tracking. This method effectively improves the dynamic performance and robustness of the multi-DOF platform, providing a reliable control solution for high-precision operations in fields such as industrial automation, precision manufacturing, and aerospace. Meanwhile, it offers new theoretical and practical references for the research on robust control of multi-DOF systems.