Robust real-time adaptive parameter estimation in nonlinear dynamical systems

Dr. Martin Guay, Chemical Engineering, Queen's University


30 September 2010 at 10:30

Location: JHE 326H

In this presentation, we present new techniques for parameter identification for nonlinear dynamical systems. The methods presented are intended to improve the performance of adaptive control systems such as real-time optimization schemes and adaptive extremum-seeking systems. Using recent results on finite-time adaptive control, we develop alternative techniques that can be used to guarantee the convergence of parameter estimates to their true values in the presence of model-mismatch and exogenous variables. A novel set-based adaptive estimation method is proposed to simultaneously estimate the parameters and the uncertainty associated with the true value. It is shown that the set-based update technique leads naturally to the development of an effective adaptive parameter estimation technique for nonlinearly parameterized nonlinear dynamical systems with guaranteed convergence of the parameter estimates to their true values. Simulation examples are described that demonstrate the effectiveness of the estimation technique. The application of the set-based technique for the development of adaptive-extremum seeking control systems and adaptive observers will also be briefly discussed.


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