An Offline Fuzzy Model-Predictive Control Approach Using Cache

In order to ease the online computational burden of fuzzy model-predictive control for the Takagi–Sugeno model with bounded disturbance, a lookup table containing the possible mappings from the state to the input is usually constructed offline so that the online computational burden is reduced to searching in this lookup table. However, with the increase in the problem size, the computational burden of the online search in the lookup table can be large enough to influence the real-time implementation. In this article, we propose a novel offline approach to solve this problem, where the control law is online searched in a receding horizon cache, which is only a small portion of the lookup table. The cache is refreshed in a one-step-ahead fashion to guarantee that the proper one-step-ahead state-to-input mapping can be found in the cache. The recursive feasibility and stability hold. The effectiveness and the efficiency of the proposed approach are verified through two examples.