A Data-Driven Dual-Rate Control Method for a Heat Exchanging Process

The heat exchanging process is a strong nonlinear and cascade industrial unit, which is effected by the large random disturbances in the steam pressure, the outdoor temperature, and the water discharged by users. To solve this problem, in this paper, a PI controller with unmodeled dynamic compensation is combined with a dual-rate control, and a dynamic model of the supply water temperature in the outer loop with linear model and unknown higher order nonlinear is established by introducing the dynamics of the closed-loop control system for the steam flow-rate with a lifting method. This is then used in designing a one-step optimal PI control algorithm with unmodeled dynamics compensation. Second, a data-driven dual-rate control method is proposed for the control of water temperature and steam flow-rate. The stability and convergence of the proposed algorithm is analyzed. Finally, both, a contrast simulated experiment with the interval intelligent cascade control algorithm and an industrial application are included to demonstrate that the proposed method can control water temperature and steam flow-rate with large random disturbances within the target range of values for process requirements.