Model predictive control (MPC) is a powerful technique that offers a range of solutions in processing contexts in a number of prominent industries. This book sets out to offer the reader the latest work in the field, showcasing new advances and pointing towards new innovations and trends. The first part offers advanced perspectives on MPC. The authors present their findings on subjects including fuzzy-neural model predictive control, genetic algorithms for improved nonlinear MPC, and MPC based on nonlinear autoregressive with exogenous inputs. Part two seeks to explore the frontiers of the field. Here, the contributors examine issues including constrained predictive control based on feedback linearization and LQ, infeasibility handling, and case studies of MPC in network control systems and the juice concentration process. This is an excellent resource for any advanced reader seeking the state-of-the-art in this important and exciting area. It offers the reader both an insight into current knowledge and many challenges and possibilities for future research.
| Specifications |
Descriptions |
| ISBN |
9789535118565 |
| Year |
2017 |
| Binding |
Hardcover |
| Subject |
Mechanical Engineering |
| Pages |
200 |
| Weight |
0.4 |
| Readership |
NA |
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