Date & Time:
Tuesday, December 18, 2012; 12:00 PM
In this presentation, an adaptive estimation technique for the estimation of time-varying parameters for a class of continuous-time nonlinear system is proposed. In the first part of the talk, we present an application of the estimation routine for the estimation of unknown heat loads and heat sinks in building systems. The technique proposed is a set-based adaptive estimation that can be used to estimate the time-varying parameters along with an uncertainty set. The proposed method is such that the uncertainty set update is guaranteed to contain the true value of the parameters. Unlike existing techniques that rely on the use of polynomial approximations of the time-varying behaviour of the parameters, the proposed technique does not require a functional representation of the time-varying behaviour of the parameter estimates.
In the second part of the talk, we consider the application of the estimation technique for the solution of a class of real-time optimization problems. It is assumed that the equations describing the dynamics of the nonlinear system and the cost function to be minimized are unknown and that the objective function is measured. The main contribution is to formulate the extremum-seeking problem as a time-varying estimation problem. The proposed approach is shown to avoid the need for averaging results which minimizes the impact of the choice of dither signal on the performance of the extremum seeking control system.
Prof. Martin Guay
Martin Guay is a Professor in the Department of Chemical Engineering at Queen's University in Kingston, Ontario, Canada. His expertise is in the area of nonlinear control systems including model predictive control, adaptive estimation and control, and geometric control. Dr. Guay is associate editor for Automatica, IEEE Transactions on Control Systems Technology and the Journal of Process Control. He is the current chair of the Process Control Technical Committee of the IEEE Control Systems Society. He was the recipient of the Syncrude Innovation award from the Canadian Society of Chemical Engineers. He also received the Premier Research Excellence award and the Queen's Chancellor's Research Award. He recently received, jointly with Dr. V. Adetola, a best paper award from the Journal of Process Control for work in the area of model predictive control and real-time optimization.