Nonlinear model order reduction for predictive control of the diesel engine airpath
| Autor: | Kenneth Butts, Jing Sun, R.B. Choroszucha |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
Nonlinear model order reduction
0209 industrial biotechnology Engineering Mathematical optimization business.industry 020208 electrical & electronic engineering 02 engineering and technology Atmospheric model Diesel engine Controllability Model predictive control 020901 industrial engineering & automation Control theory Nonlinear model 0202 electrical engineering electronic engineering information engineering Observability business Gramian matrix |
| Zdroj: | ACC |
| DOI: | 10.1109/acc.2016.7526159 |
| Popis: | In this paper, balanced truncation based on empirical gramians is explored for nonlinear model order reduction of a diesel airpath (DAP) model to facilitate effective nonlinear model predictive control (NMPC) design and implementation. Several issues are identified for the standard empirical gramian formulations, especially for the DAP model whose inputs, states, and outputs are constrained and have very different scales, and a modified formulation of the empirical gramians to mitigate the issues is proposed. The reduced order model, derived using balanced truncation based on the proposed empirical gramian, is applied to design the NMPC for the DAP system. The resulting performance is evaluated through simulations and compared with those obtained using other gramian based nonlinear model order reduction methods to demonstrate the effectiveness of the proposed approach. |
| Databáze: | OpenAIRE |
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