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This paper focuses on the problem of Kalman filtering for Itô stochastic continuous-time systems with multiple delayed measurements, for which very little work exist to date. For an Itô-stochastic system, its stochastic differential and integral have a significant place and are different from other stochastic systems owing to the Wiener or the Brownian process. In this paper, an Itô stochastic continuous-time system with multiple delayed measurements is first reduced to a system with delay free measurements by applying the stochastic analysis and calculus of stochastic variables. Next, the Itô differentials for the optimal filter and its error variance are derived. Finally, through an illustrative example, the performance of the designed optimal filter is verified.

In heating, ventilating and air-conditioning (HVAC) systems, there exist severe nonlinearity, time-varying nature, disturbances and uncertainties. A new predictive functional control based on Takagi-Sugeno (T-S) fuzzy model was proposed to control HVAC systems. The T-S fuzzy model of stabilized controlled process was obtained using the least squares method, then on the basis of global linear predictive model from T-S fuzzy model, the process was controlled by the predictive functional controller. Especially the feedback regulation part was developed to compensate uncertainties of fuzzy predictive model. Finally simulation test results in HVAC systems control applications showed that the proposed fuzzy model predictive functional control improves tracking effect and robustness. Compared with the conventional PID controller, this control strategy has the advantages of less overshoot and shorter setting time, etc.

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