For parallel manipulators, traditional trajectory tracking techniques suffer from input saturation and external disturbances, which results in poor transient responsiveness and decreased control accuracy. In order to guarantee quick and reliable trajectory tracking under such limitations, this study suggests an improved control approach that combines adaptive barrier functions with terminal sliding mode control. First, a compensator is added to lessen the consequences of input saturation. Then, for finite-time tracking, a new terminal sliding surface is constructed, which is based on tracking error and an auxiliary variable connected to the compensator. To reject time-varying disturbances, the adaptive barrier function is further expanded. The whole system’s finite-time stability is guaranteed by applying Lyapunov theory. The enhanced tracking performance of the proposed method over traditional approaches is demonstrated by simulation results. Compared to SOSMC and NTSMC, the proposed controller achieves up to 14% improvement in performance indices and 31% faster convergence, highlighting its effectiveness for precise trajectory tracking in parallel robots. Additionally, the effectiveness of the suggested controller is validated by real-time experiments on a physical parallel manipulator. The resilience of the approach against real-world uncertainties, including sensor noise, unmodeled dynamics, and actuator nonlinearities, is confirmed by this high correlation. All things considered, the suggested method provides a dependable and effective way to track trajectories in applications requiring a high degree of precision and utilizing parallel manipulators.
Barghandan et al. (Fri,) studied this question.