A minimum error entropy controller is developed for superheated vapour temperature control of a waste heat recovery process using Organic Rankine cycles (ORC). A nonlinear dynamic model is briefed for the ORC evaporator to capture the key dynamic characteristics of the process. Considering non-Gaussian disturbance terms, the control objective is proposed to minimize the combined entropy function and the mean value of the squared tracking errors. The controller is designed by taking into account of bounded constraints on input actions. The improved performances of the proposed method in reducing control variation and decreasing tracking error uncertainty are discussed by a comparison with standard PID control through simulation study conducted on an ORC waste heat recovery process.
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