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This paper presents a two-level controller based on neural network for wastewater treatment process. Predictive optimal control scheme using neural network is applied in the upper level control unit. The optimization unit is designed to generate trajectories of oxygen concentration and heterotrophic concentration. A feed-forward neural network is employed as prediction model. The gradient descent...
A multi-variable dynamic model of the glutamic acid fermentation process based on neural network is established. Combining the off-line Optimal control method and the on-line adaptive fuzzy neural network control method, the hybrid fuzzy adaptive fermentation process control model is designed. The off-line optimization track is the main control model, while the adaptive fuzzy neural network based...
This work presents a solution to solve industrial cranes kinematic control problem also called automatic travel control (ATC) [10]. Aspects such as optimal trajectory reference calculation considering: process cycle time and distance travelled minimization, improvements in mechanical transmission systems useful life, prohibited areas and obstacles in the crane workspace, etc., and load position control...
Aiming at the complexity of the glutamic acid fermentation process, a neural network dynamic model of the fermentation process was established. The improved differential evolutionary algorithm (DEA) was used to the multi-variables optimal control of the fermentation process and the optimal control trajectories of operating variables were found out. Some improvements of the primitive DEA were made...
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