Sliding Mode Control: Evolution, Advanced Strategies, and Future Research Directions

Abstract

Sliding Mode Control (SMC) is a widely adopted nonlinear control methodology for systems affected by parameter uncertainties, external disturbances, and modeling inaccuracies. Originating from Variable Structure Control (VSC) in the late 1950s, SMC has evolved significantly to improve robustness, reduce chattering, enhance convergence performance, and address the challenges of modern engineering systems. This paper presents an overview of the evolution and advanced strategies of SMC, highlighting its fundamental concepts, mathematical formulation, stability characteristics, advantages, limitations, and practical applications. The development of classical first order SMC, higher-order SMC, terminal and non-singular terminal SMC, adaptive SMC, integral SMC, observer-based SMC, and disturbance observer-based SMC is discussed. Recent advancements, including intelligent SMC, learning-based SMC, fractional-order SMC, and event-triggered SMC, are also reviewed with emphasis on their role in improving adaptability and implementation efficiency. Furthermore, emerging applications of SMC in robotics, autonomous systems, renewable energy, power electronics, and cyber-physical systems are highlighted. The paper also identifies key research challenges, including chattering reduction, computational complexity, stability analysis of intelligent methods, and real-time implementation. Finally, future research directions are discussed toward developing more adaptive, efficient, and intelligent SMC frameworks for complex uncertain systems.