Ali Javadi, Hamed Haghighi, Khemwutta Pornpipatsakul, R. Chaichaowarat
{"title":"Data-Driven Position and Stiffness Control of Antagonistic Variable Stiffness Actuator Using Nonlinear Hammerstein Models","authors":"Ali Javadi, Hamed Haghighi, Khemwutta Pornpipatsakul, R. Chaichaowarat","doi":"10.3390/jsan13020029","DOIUrl":null,"url":null,"abstract":"In this paper, an optimal PID controller is introduced for an antagonistic variable stiffness actuator (AVSA) based on Hammerstein models. A set of Hammerstein models is developed for the AVSA using the voltage difference method. For each stiffness level, linear and nonlinear Hammerstein models are identified using the least squares method. Experimental results confirm that the outputs of the Hammerstein models fit the measured data better than linear models, as Hammerstein models can incorporate nonlinear effects such as friction. A genetic algorithm is utilized to find optimal PID gains for different stiffness levels and reference position amplitudes. The final gains are obtained by linearly interpolating the optimal gains obtained. To demonstrate the effectiveness of the proposed design, several scenarios with different reference positions and stiffness profiles are provided. Specifically, square, sinusoidal, and sawtooth waves are used for reference positions and stiffness values. The robustness of the proposed approach is further analyzed by applying a disturbance force on the actuator link. The results are compared with the linear method, showing that the proposed design can handle soft transitions in stiffness variation and ensure perfect tracking.","PeriodicalId":3,"journal":{"name":"ACS Applied Electronic Materials","volume":" 2","pages":""},"PeriodicalIF":4.3000,"publicationDate":"2024-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Applied Electronic Materials","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3390/jsan13020029","RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0
Abstract
In this paper, an optimal PID controller is introduced for an antagonistic variable stiffness actuator (AVSA) based on Hammerstein models. A set of Hammerstein models is developed for the AVSA using the voltage difference method. For each stiffness level, linear and nonlinear Hammerstein models are identified using the least squares method. Experimental results confirm that the outputs of the Hammerstein models fit the measured data better than linear models, as Hammerstein models can incorporate nonlinear effects such as friction. A genetic algorithm is utilized to find optimal PID gains for different stiffness levels and reference position amplitudes. The final gains are obtained by linearly interpolating the optimal gains obtained. To demonstrate the effectiveness of the proposed design, several scenarios with different reference positions and stiffness profiles are provided. Specifically, square, sinusoidal, and sawtooth waves are used for reference positions and stiffness values. The robustness of the proposed approach is further analyzed by applying a disturbance force on the actuator link. The results are compared with the linear method, showing that the proposed design can handle soft transitions in stiffness variation and ensure perfect tracking.
期刊介绍:
ACS Applied Electronic Materials is an interdisciplinary journal publishing original research covering all aspects of electronic materials. The journal is devoted to reports of new and original experimental and theoretical research of an applied nature that integrate knowledge in the areas of materials science, engineering, optics, physics, and chemistry into important applications of electronic materials. Sample research topics that span the journal's scope are inorganic, organic, ionic and polymeric materials with properties that include conducting, semiconducting, superconducting, insulating, dielectric, magnetic, optoelectronic, piezoelectric, ferroelectric and thermoelectric.
Indexed/Abstracted:
Web of Science SCIE
Scopus
CAS
INSPEC
Portico