Sliding Mode Control

Sliding mode control (SMC) is a robust control technique aiming to maintain system trajectories within a predefined sliding surface, ensuring stability and performance despite uncertainties and disturbances. Current research emphasizes adaptive SMC strategies, often incorporating deep reinforcement learning, neural networks, or backstepping techniques to enhance adaptability and reduce chattering, particularly in complex systems like robots, UAVs, and underwater vehicles. These advancements are significantly improving the control of underactuated systems and those operating in challenging or unpredictable environments, with applications ranging from robotics and aerospace to industrial automation. The focus on finite-time convergence and singularity avoidance further enhances the practical applicability of SMC in real-world scenarios.