A Cascade Multiple-Model Predictive Controller of Nonlinear Systems by Integrating Stability and Performance

To deal with strong nonlinearity in nonlinear systems, a new method called cascade multiple-model predictive controller based on gap metric and stability margin, is proposed. The gap metric is utilized to describe the nonlinear system by a linear model bank. It is possible to select nominal local mo...

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Bibliographic Details
Main Authors: Rikhtehgar, Pouya, Ahmadi, Mahdi, Haeri, Mohammad
Format: Conference Proceeding
Language:English
Subjects:
Closed loop systems
Computer simulation
Gap metric
integrating stability and performance
model predictive stabilizer controller
multiple-controller
Nonlinear control systems
Predictive control
Proportional control
Robust control
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Summary:To deal with strong nonlinearity in nonlinear systems, a new method called cascade multiple-model predictive controller based on gap metric and stability margin, is proposed. The gap metric is utilized to describe the nonlinear system by a linear model bank. It is possible to select nominal local models from the linear model bank by an algorithm based on the gap metric and stability margin to avoid the redundancy of the local controllers. By scheduling proportional controller for each nominal local model, the robust stability is guaranteed whereas there will be no guarantee for the desired performance. Then, by designing a model predictive controller in the cascade structure, the closed loop performance is improved. The achievements of the proposed method are illustrated by computer simulations.
ISSN:2642-9527
DOI:10.1109/IranianCEE.2019.8786675