Patent ID: 7085692

Claim:
In a system using multiple smart matter dynamic controllers, each controller comprising one or more actuator-sensor pairs, a method for dynamic control of the system, comprising: representing each controller using one or more control system models; executing each of control system models and predicting future performance of the system after one or more time intervals as a weighted sum of individual predictions of each model for each controller; measuring actual performance of the system after said one or more time intervals; for each controller, computing a prediction error as the difference between the predicted performance and the measured actual performance of the subsystem controlled by the controller; adjusting the weights of at least two control system models based on their prediction errors relative to the prediction errors of other models wherein adjusting the weights of at least two control system models includes increasing a weight of at least one control system model in the plurality of control system models relative to a weight of at least one other model; and using the control system models and the adjusted weights in the dynamic controllers for dynamic control of the system during next time interval, wherein adjusting the weights of at least two control system models includes defining a fraction a i of a weight w i , of an i th model, where 0<a i <1, which will be adjusted for the next time interval, wherein each model is used to predict, at a current time t, a future state of the system at a later time (t+Δt): x i (t+Δt;x(t),u(t)), where x(t) is a state of the system at time t,x i (t+Δt) is a state of the system at time t+Δt estimated by the i th model, and u(t) is a control input at time t, the method further comprising assigning a new weight w i new for the i th model according to the formula w i n ⁢ ⁢ e ⁢ ⁢ w = ( 1 - a ) ⁢ w i o ⁢ ⁢ l ⁢ ⁢ d + a [ 1 / ( e i 2 + σ 2 ) ∑ j = 1 N ⁢ 1 / ( e j 2 + σ 2 ) ] where w i old is a previous weight for the i th model, e i is a prediction error of the i th model, and σ 2 is a noise variance of the multiple actuator-sensor smart matter dynamic control system.