Moving horizon control and estimation of livestock ventilation systems and indoor climate

In this paper, a new control strategy involves exploiting actuator redundancy in a multivariable system is developed for rejecting the covariance of the fast frequency disturbances and pursuing optimum energy solution. This strategy enhances the resilience of the control system to disturbances beyond its bandwidth and reduce energy consumption through on-line optimization computation. The moving horizon estimation and control (also called predictive control) technology is applied and simulated. The design is based on a coupled mathematical model which combines the hybrid ventilation system and the associated indoor climate for poultry in barns. The comparative simulation results illustrate the significant potential and advancement of the moving horizon methodologies in estimation and control for nonlinear Multiple Input and Multiple Output system with unknown noise covariance and actuator saturation.