In recent years, many techniques for parameter estimation have been developed, with special attention given to the case of time-varying parameters, as they can describe a wide range of physical systems. However, a common requirement is the full-availability of the system states, a condition that may not be fulfilled in some applications. This paper proposes a robust parameter estimation technique for Linear Parameter-Varying (LPV) systems, considering the non-availability of all states and the influence of bounded disturbances. A robust filter with the generalized H2 norm is designed to reconstruct the state vector, based on Linear Matrix Inequalities (LMIs), while a robust adaptive law is formulated to address parameter computation. The convergence of the procedure is proven to be globally uniformly ultimately bounded (GUUB). Numerical experiments are conducted with meta-heuristic optimization to tune the hyperparameters of the adaptive law, highlighting the effectiveness of the proposed methodology in estimating the system parameters.
Silva et al. (Thu,) studied this question.