Predictive Control for Linear and Hybrid Systems
University of California, Berkeley · IMT School for Advanced Studies Lucca · +1 more institution
Abstract
Model Predictive Control (MPC), the dominant advanced control approach in industry over the past twenty-five years, is presented comprehensively in this unique book. With a simple, unified approach, and with attention to real-time implementation, it covers predictive control theory including the stability, feasibility, and robustness of MPC controllers. The theory of explicit MPC, where the nonlinear optimal feedback controller can be calculated efficiently, is presented in the context of linear systems with linear constraints, switched linear systems, and, more generally, linear hybrid systems. Drawing upon years of practical experience and using numerous examples and illustrative applications, the authors…
Citation impact
- FWCI
- 58.64
- Percentile
- 100%
- References
- 248
Authors
3Topics & keywords
- Model predictive control
- Computer science
- Robustness (evolution)
- Toolbox
- MATLAB
- Control engineering
- Linear programming
- Linear system
- Industry, innovation and infrastructure