Predictive Control of Dissolved Oxygen Concentration in Cynoglossus Semilaevis Industrial Aquaculture

Dissolved oxygen is an important factor that influences cynoglossus semilaevis’ growth. Keeping the stability of its concentration is beneficial for cynoglossus semilaevis’ healthy growth. The changing process of dissolved oxygen concentration contains nonlinearities and big time- delay because it is restricted by multiple factors, so traditional control methods are difficult to control it effectively or keep its concentration stable. This paper proposes a predictive control model for dissolved oxygen based on DMC algorithm. Firstly, it adopts DMC’s predictive model to predict the dissolved oxygen concentration’s variation trend. Secondly, it gives the calculated optimal control to aerators. Using DMC predictive model, it has better solved the nonlinear prediction problem of dissolved oxygen. Using DMC rolling optimization, it has better solved the optimal control problem of dissolved oxygen. System simulation results have shown that the model this paper proposed has a good performance in terms of rapidity, disturbances and errors in dissolved oxygen control.