Process Integrated Design within a Model Predictive Control Framework
| Authors: | Francisco Mario, University of Salamanca, Spain
Vega Pastora, University of Salamanca, Spain
Pérez Omar, University of Simón Bolívar, Venezuela |
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| Topic: | 2.1 Control Design |
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| Session: | Predictive Control: Implementation and Applications |
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| Keywords: | process integrated design, predictive control, controllability, nonlinear optimization, stochastic optimization |
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Abstract
In this work the integrated design of the activated sludge process in a wastewater treatment plant has been performed, including a linear multivariable predictive controller (MPC) with constraints. In the integrated design procedure, the process parameters are obtained simultaneously with the parameters of the control system by solving a multiobjective constrained non-linear optimization problem, and taking into account investment and operation costs. The mathematical optimization for tuning all parameters is tackled in two iterative steps. First, plant parameters are obtained using a sequential quadratic programming (SQP) method, and secondly, a type of random search method is used to tune the controller parameters (horizons and weights) . Due to the difficulty to measure some variables, there has been also developed a Kalman Filter for state estimation
