Sliding-Mode Control With Soft Computing: A Survey

TLDR

Sliding‑mode control has been widely used for over 50 years due to its simplicity and robustness, yet key technical problems persist, prompting recent integration with soft computing to address these challenges. This survey reviews recent developments in sliding‑mode control systems that incorporate soft computing, highlighting key research issues and future directions. The authors examine the state of the art of SMC–SC integration, evaluating how adaptive learning and control techniques mitigate the technical challenges of sliding‑mode control.

Abstract

Sliding-mode control (SMC) has been studied extensively for over 50 years and widely used in practical applications due to its simplicity and robustness against parameter variations and disturbances. Despite the extensive research activities carried out, the key technical problems associated with SMC remain as challenging research questions due to demands for new industrial applications and technological advances. In this respect, soft computing (SC) is a rather recent development in intelligent systems which has provided alternative means for adaptive learning and control to overcome the key SMC technical problems. Substantial efforts in integration of SMC with SC have been placed in recent years with various successes. In this paper, we provide the state of the art of recent developments in SMC systems with SC, examining key technical research issues and future perspectives.