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Robust Constrained Model Predictive Control for Nonlinear Systems: AComparative Study

Author(s):

M. Kothare, V. Nevistic, M. Morari
Conference/Journal:

vol. AUT95-13
Abstract:

We compare two different approaches to controlling nonlinear systems using model predictive control (MPC) techniques. In the first approach, we approximate the nonlinear system by a linear time-varying (LTV) system and design a stabilizing receding horizon state-feedback control law using optimization techniques based on linear matrix inequalities (LMIs). In the second approach, we use an inner feedback loop to linearize the nonlinear plant and use the resulting linear model to synthesize a controller strategy based on standard MPC techniques. However, the constraints in this case are nonlinear and the resulting nonlinear optimization must be solved using some iterative technique. We compare the performance of these two different approaches by applying them to an example plant.

Year:

1995
Type of Publication:

(04)Technical Report
Supervisor:



No Files for download available.
% Autogenerated BibTeX entry
@TechReport { KotNev:1995:IFA_1485,
    author={M. Kothare and V. Nevistic and M. Morari},
    title={{Robust Constrained Model Predictive Control for Nonlinear
	  Systems: AComparative Study}},
    institution={},
    year={1995},
    number={},
    address={},
    url={http://control.ee.ethz.ch/index.cgi?page=publications;action=details;id=1485}
}
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