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The method described makes it possible to assign weights to important priority factors by the use of control variables. A function that in part measures the deviation from a desired system state is optimized by the choice of values of these control variables. Under the assumption that Equation 5 represents the dynamics of the system, Equation 8 provides the system with an input that minimizes the performance index P of Equation 6. This input, u, can then be used in Equation 1, yielding the desired sequencing function. The control exercized is adaptive in the sense that the representation of the system's dynamics is periodically revised by successive least-squares fits of a new data as required.
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