Experimental validation of a continuous-time MCSI algorithm with bounded adaptive gains

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Abstract

Model reference adaptive control algorithms with minimal controller synthesis have proven to be an effective solution to tame the behaviour of linear systems subject to unknown or time-varying parameters, unmodelled dynamics and disturbances. However, a major drawback of the technique is that the adaptive control gains might exhibit an unbounded behaviour when facing bounded disturbances. Recently, a minimal controller synthesis algorithm with an integral part and either parameter projection or σ-modification strategies was proposed to guarantee boundedness of the adaptive gains. In this article, these controllers are experimentally validated for the first time by using an electro-mechanical system subject to significant rapidly varying disturbances and parametric uncertainty. Experimental results confirm the effectiveness of the modified minimal controller synthesis methods to keep the adaptive control gains bounded while providing, at the same time, tracking performances similar to that of the original algorithm.

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Montanaro, U., Costa-Castelló, R., Olm, J. M., & Larco-Barros, C. (2019). Experimental validation of a continuous-time MCSI algorithm with bounded adaptive gains. Journal of the Franklin Institute, 356(12), 5881–5897. https://doi.org/10.1016/j.jfranklin.2019.03.012

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