Multivariable predictive controller with excitation constraint for closed-loop identification. / Controlador preditivo multivariável com restrição de excitação para identificação de processos em malha fechada.

AUTOR(ES)

Sérgio Luiz Ballin

DATA DE PUBLICAÇÃO

2008

RESUMO

In MPC implementation, the process models development and definition is the most critical and time consuming task. Normally, the models are obtained through plant identification tests where perturbations are individually introduced in the manipulated variable while the controlled variable open-loop behavior is observed. For this reason, the application of closed-loop identification techniques to MPC controllers with input or output constraints is a growing interest area. This work studies the traditional MPC controller modification with the inclusion of a new excitation constraint, in addition to input or output constraints, whose function is to perturb the process in a controlled way, permitting the closed-loop identification of more precise models, based on known approximated models. Four implementation methodologies are developed and some simulated theoretical cases are presented using models of two industrial processes extracted from recent papers related to multivariable control with models uncertainty. The simulation results show that the obtained datasets allow the identification of the correct model, both in the nominal case (when the model used by MPC is the true model of the plant) and in the uncertain case, where the model used by MPC is different from the true model.

ASSUNTO(S)

closed-loop identification controle preditivo system identification process control controle de processos predictive control identificação (teoria de sistemas e controle)

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