Fuzzy-High-Gain Observer for States and Unknown Inputs Estimation of an Activated Sludge Process

Considering how crucial variables assessment is in systems’ control, especially states and inputs, this work addresses the simultaneous estimate problem of non-measured states and unknown inputs (UIs) of an activated sludge process (ASP). A fuzzy high gain observer (FHGO) is designed to detect concentrations during aerobic and anoxic phases with accuracy and economy. There are only two provided states, which are the oxygen concentration and the nitrate concentration. While the others are deemed unavailable. Simulation results show that the proposed observer converges asymptotically and yields a good reconstruction of the unknown inputs, which are the ammonia input concentration, and the substrate input concentration. Experimental data has been exploited also to confirm the effectiveness of the suggested FHGO.