Enhanced confidence control based on non-linear mathematics models of biological process in the urban wastewater treatment systems

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(1)For the first year to the second year, we established individual element technology such as making a practical modeling for wastewater treatment process, adaptive observer, and sensing technology.(2) For the last year, we have proposed the enhanced confidence control system. This last proposed control system is possible to meat the request of practical use, optimality, robustness, reliability, flexibility, and realization. This control system of activated sludge process consists of two layers of control systems, i.e., upper level control and lower level controller, The upper level controller optimizes the whole process, on the other hand, the lower level controller generates the control input locally.(3) In the upper level controller, we proposed two constructing methods. (3-1) The weight coefficients in a certain cost function are determined for the nonlinear-optimization problem, then it is successful in designing the control system that utility was kept. (3-2) we applied the extr … More eme control strategy for the activated sludge process. We succeeded in a method of forming of control system to do hold in extreme value of the cost function with on-line manner.(4) In the lower level controller, we proposed three constructing methods. (4-1) We evaluate the reliability of the water sensor of ammonia indicator and nitric acid indicators. Then the tuning method of PI control parameters is proposed. We did enforcement experiment by a pilot plant and examined the problem that should have been settled. (4-2) It is successful by introducing passivity into elucidation of positive system problem. (4-3) The new adaptive observer method is proposed, the total stability of this observer system is proven theoretically.(5) We proposed a reduced-order model of biological wastewater treatment process for the purpose of model-based control design of nitrogen and phosphorus removal. By perturbation technique with ASM2 model, we derive the lower order system whose response is as same as one of original system. Less