Model Predictive ControlSpringer Science & Business Media, 6 dic 2012 - 280 páginas In recent years Model Predictive Control (MPC) schemes have established themselves as the preferred control strategy for a large number of processes. Their ability to handle constraints and multivariable processes and their intuitive way of posing the pro cess control problem in the time domain are two reasons for their popularity. This volume by authors of international repute provides an extensive review concerning the theoretical and practical aspects of predictive controllers. It describes the most commonly used MPC strategies, especially Generalised Predictive Control (GPC), showing both their theoretical properties and their practical implementation issues. Topics such as multivariable MPC, constraint handling, stability and robustness properties are thoroughly analysed in this text. |
Índice
Generalized Predictive Control | 4 |
Prediction Model | 12 |
Commercial Model Predictive Control Schemes | 33 |
R R | 65 |
Simple Implementation of GPC for Industrial Processes | 84 |
Multivariable Processes | 131 |
Constrained | 167 |
Robust | 209 |
Applications | 229 |
A Revision of the Simplex method | 258 |
| 275 | |
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algorithm applied Au(t b₁ behaviour calculated chapter closed loop computed considered constant constraints control actions control effort control horizon control increments control law control objectives control sequence control signal control system controller coefficients controller parameters corresponding cost function dead defined delay described Diophantine equation dynamics equal error expressed feasible filter flow flowrate formulation free response frequency future control given implementation impulse response industry inputs and outputs instant limits linear model manipulated variables measurable disturbances minimize Model Predictive Control multivariable N₁ N₂ noise nominal Notice objective function obtained operating point outlet temperature overshoot past inputs perturbations pole polynomial matrix predicted outputs prediction horizon predictor quadratic quadratic function receding horizon recursively reference trajectory robustness sampling seen setpoint shown in figure slew rate solution solved stability standard GPC static gain step response strategy superposition principle transfer function uncertainties valve vector zero