Abstract
This paper presents a novel direct model reference adaptive control scheme using a decentralized update law for nonsquare Euler-Lagrange systems. The proposed decentralized adaptation law is based on the simple adaptive control (SAC) methodology in which the control gain matrices are updated by the reference model input and state signals, and by the errors between the nonlinear system and a reference model. Numerical simulation results are presented to illustrate the trajectory tracking performance of the proposed approach in comparison with both a decentralized modified simple adaptive control (DMSAC) and a fuzzy logic-based direct adaptive control strategy. Results demonstrate that the designed adaptive control approach achieves improved tracking results compared to the DMSAC and fuzzy logic control methodologies.
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