Model predictive control: theory and practice—a survey
Automatica (Journal of IFAC)
Model Predictive Control in the Process Industry
Model Predictive Control in the Process Industry
Optimization of enzymatic hydrolysis of leather waste
AIC'06 Proceedings of the 6th WSEAS International Conference on Applied Informatics and Communications
Synthesis of explicit model predictive control system with feasible region shrinking
ROCOM'08 Proceedings of the 8th WSEAS International Conference on Robotics, Control and Manufacturing Technology
Multiple modeling and fuzzy predictive control of a tubular heat exchanger system
WSEAS Transactions on Systems and Control
Identification of non-linear systems, based on neural networks, with applications at fuzzy systems
ICAI'09 Proceedings of the 10th WSEAS international conference on Automation & information
Applied Optimization with MATLAB Programming
Applied Optimization with MATLAB Programming
Technical Communique: Who needs QP for linear MPC anyway?
Automatica (Journal of IFAC)
Brief An algorithm for multi-parametric quadratic programming and explicit MPC solutions
Automatica (Journal of IFAC)
Comparison of artificial neural networks using prediction benchmarking
ACMOS'11 Proceedings of the 13th WSEAS international conference on Automatic control, modelling & simulation
Identification of Arrhenius equation parameters for control purposes
ACMOS'11 Proceedings of the 13th WSEAS international conference on Automatic control, modelling & simulation
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The article deals with the control of the semi-batch reactor that is used in chromium waste recycling process based on the enzymatic hydrolysis. The chromium waste comes from the chromium salt tanning while processing the natural leather. The recycling technique separates chrome in the form of chromium filter cake from protein. All products of this procedure are utilisable thus it is a waste free technology. The reactor deals with a problem of chromium sludge (chromium filter cake) reusing. However, the control of the semi-batch reactor is highly complex because the chemical reaction in the reactor is strongly exothermic and the in-reactor temperature is rising very fast depending on the reaction component dosing. To simulate the real process a mathematical model including reaction kinetics was used. The parameters of the achieved model were obtained and verified by experiments. Three different approaches are applied to the temperature control problem: two step control without and with penalization, PID control and model predictive control. The system control is generally difficult because of its nonlinear behaviour.