Finite‐Time Sliding Mode Control for Uncertain Robotic Systems Using a Novel Exponential‐Like Reaching Law

ABSTRACT In this paper, we present a finite‐time sliding mode control method for trajectory tracking control of uncertain robotic systems. First, to dispel the conflict between high convergence speed and reduced chattering in sliding mode control (SMC), a novel exponential‐like reaching law (ELRL) is designed by imposing dual prescribed performance on the tracking error and the sliding mode variable, respectively. The proposed ELRL replaces the sign function with an exponential‐like term. By doing so, the system state can be accelerated faster to the sliding mode surface within prescribed transient and steady‐state performance, while mitigating chattering. Second, to approximate and compensate for model parameter uncertainties and strong external disturbances, an unknown system dynamic estimator (USDE) adopting first order filter technique is presented to estimate lumped disturbance. Then, by incorporating the USDE into the SMC, a finite‐time sliding mode control method is developed for robotic systems. Its semi‐globally practically finite‐time stability is strictly proved via Lyapunov theory. Finally, comparative experiments are conducted on a simulated robotic system, illustrating faster convergence speed, stronger robustness, and greater chattering mitigation of the proposed method.