(712h) Economic Performance Improvement for Lyapunov-Based Economic Model Predictive Control Using Disturbance Probability Distributions
Motivated by the above considerations, we propose an LEMPC design in which the region in state-space within which time-varying operation is allowable is expanded compared to the traditional LEMPC design by accounting for the probability distribution of the disturbance magnitude (rather than assuming that the upper bound occurs throughout the entire sampling period). Specifically, the region in which time-varying operation is allowed is chosen such that if the disturbance at any given time throughout a sampling period takes a value within its bounds with a probability P according to a disturbance probability distribution obtained from routine process operating data, then the closed-loop state is maintained within the stability region throughout the sampling period. The role that the probability distribution shape plays in the size of the region of time-varying operation is evaluated, and the closed-loop stability and feasibility properties of this less conservative LEMPC design are investigated. Practical suggestions are made for obtaining a disturbance magnitude probability distribution and for designing the LEMPC when the probability distribution itself has uncertainty since it is obtained from limited process data. A chemical process example is used to evaluate the economic benefits of designing the LEMPC with a less conservative state constraint activating the first or second mode of operation compared to the traditional LEMPC design methodology.
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