Abstract
We compare two approaches to controlling nonlinear systems using model predictive control (MPC) techniques. In the first 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. The nonlinear constraints resulting from the feedback linearization are handled using an iterative method. In the second 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).
| Original language | English (US) |
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| Title of host publication | Proceedings of the IEEE Conference on Decision and Control |
| Publisher | IEEE |
| Pages | 2884-2885 |
| Number of pages | 2 |
| Volume | 3 |
| State | Published - 1995 |
| Externally published | Yes |
| Event | Proceedings of the 1995 34th IEEE Conference on Decision and Control. Part 1 (of 4) - New Orleans, LA, USA Duration: Dec 13 1995 → Dec 15 1995 |
Other
| Other | Proceedings of the 1995 34th IEEE Conference on Decision and Control. Part 1 (of 4) |
|---|---|
| City | New Orleans, LA, USA |
| Period | 12/13/95 → 12/15/95 |
ASJC Scopus subject areas
- Chemical Health and Safety
- Control and Systems Engineering
- Safety, Risk, Reliability and Quality