Abstract
This paper deals with the design and implementation of a Model Predictive Control (MPC) algorithm for an industrial recirculating cooling water system. The plant is composed of three large reservoirs, four pumping units, three cooling towers with modulating fans, and a piezometric tower. A physical model of the system has been derived from balance equations and has been validated with experimental data. Then, a nonlinear state observer has been developed to estimate unmeasured quantities, such as the water flow rates and temperatures recirculating from the utilities. Finally, an MPC algorithm has been designed by reformulating the original nonlinear system in terms of a linear time-varying one to improve the computational efficiency of the method. The presence of on/off actuators, pumps, and fans, makes the resulting optimization problem a Mixed Integer Quadratic Programming one. Extensive simulation results and comparisons with the relay-based control scheme currently implemented witness the potentialities of the proposed solution in terms of energy savings, better control, and lifetime of the equipments. The proposed MPC algorithm is currently being tested on the real plant, its very satisfactory performance confirm the results of the simulation experiments.
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