Hybrid nonlinear model predictive control of a cooling water network. (April 2020)

• Record Type: Journal Article
• Authors: Viljoen, J.H.; Muller, C.J.; Craig, I.K.
• Is Part Of: Control engineering practice. Volume 97(2020)
• Publication Date: 2020-04
• Subjects: Nonlinear model predictive control -- Cooling tower -- Cooling water network -- Optimisation -- Gradient descent -- Hybrid systems -- Electricity consumption minimisation; Automatic control -- Periodicals; 629.89
• DOI: 10.1016/j.conengprac.2020.104319
• Languages: English
• ISSNs: 0967-0661

Abstract

Abstract: A Hybrid Nonlinear Model Predictive Control (HNMPC) strategy is developed for temperature control and power consumption minimisation of a cooling water network. The HNMPC uses a gradient descent optimisation algorithm for the continuous manipulated variables, and an enumerated tree traversal algorithm to control and optimise the Boolean manipulated variables. The HNMPC is subjected to disturbances similar to those experienced on a real plant, and its performance compared to a continuous Nonlinear Model Predictive Control (NMPC) and two base case scenarios. Power consumption is minimised, and process temperature disturbances are successfully rejected. Monetary benefits of the HNMPC control strategy are estimated.