A Study of Variable Structure and Sliding Mode Filters for Robust Estimation of Mechatronic Systems
S. Andrew Gadsden, Mohammad Al‐Shabi
20202020 IEEE International IOT, Electronics and Mechatronics Conference (IEMTRONICS)22 citationsDOI
Abstract
In this paper, a study of estimation strategies based on variable structure and sliding mode theory is performed. The smooth variable structure filter (SVSF) and the new sliding innovation filter (SIF) are based on similar sliding mode concepts but with some notable differences. The relevant literature and background are explored and the SVSF and SIF estimation algorithms are presented. For comparison purposes, the two estimation strategies are applied on a mechatronic system. The results indicate that although both the SVSF and SIF provide robust estimates to faults, the SIF formulation provides slightly more accurate estimates while maintaining robustness, and is less computationally complex.
Topics & Concepts
Robustness (evolution)MechatronicsControl theory (sociology)Variable (mathematics)Mode (computer interface)Variable structure controlComputer scienceSliding mode controlFilter (signal processing)Robust controlControl engineeringEngineeringMathematicsControl systemNonlinear systemPhysicsControl (management)Artificial intelligenceElectrical engineeringGeneChemistryQuantum mechanicsOperating systemBiochemistryMathematical analysisComputer visionTarget Tracking and Data Fusion in Sensor NetworksFault Detection and Control SystemsStructural Health Monitoring Techniques