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The practical implementation of min-max MPC (MMMPC) controllers is limited by the computational burden required to compute the control law. This problem can be circumvented by using approximate solutions or upper bounds of the worst possible case of the performance index. In a previous work, the authors presented a computationally efficient MMMPC control strategy in which a close approximation of...
This paper shows the application of a Min-Max Model Predictive Control (MMMPC) strategy to a pilot plant in which the temperature of a reactor is controlled. An approximation of the worst case cost is used to obtain the control action. This approximation can be easily computed yielding a solution of the min-max problem very close to the exact one. The complexity of the algorithm allows the real time...
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