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guidance, flight mechanics and trajectory optimization

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of the p <strong>and</strong> $ equations (i.e., Eqs. (2.5.106A) <strong>and</strong> (2.5.111) with the<br />

initial condition of Eq. (2.5.112B), the terminal condition of Eq. (2.5.106~)<br />

<strong>and</strong> with A selected so that Ptt,) satisfies the terminal variance<br />

constraint which is imposed.<br />

In.most cases, the solution will have to be achieved iteratively.<br />

Thus, the process might proceed as follows:<br />

(1) Guess the diagonal matrix A . As has been noted, the number of<br />

independent diagonal elements (i.e., the number of different<br />

quantities that can be guessed) is equal to the number of terminal<br />

constraints imposed. For example, if Eq. (2.5.87A) is used,<br />

then only one constraint is imposed <strong>and</strong> all the diagonal elements<br />

of -A are equal to some number, say A-. This number would be<br />

guessed to start the iteration.<br />

(2) Integrate the equation for Zi backwards in time with s (&+,) = n<br />

C i.e., integrate Eq. (2.5.106A) 1 .<br />

(3) Set p&J = ;,;z<strong>and</strong> integrate the P equation forward from<br />

*, to t, [i.e., Eq. (2.5.111) I.<br />

(4) Test P 14)to see if the specified terminal constraints are<br />

satisfied.<br />

(5) ze;hT2;onstraints are not satisfied, adjust h <strong>and</strong> go back to<br />

.<br />

Since the terminal constraints are inequality constraints [see<br />

Eq. (2.5.87)] , this iteration scheme will not lead to a unique solution.<br />

However, it can be shown, using st<strong>and</strong>ard methods from the Calculus of<br />

Variations, that A must be a negative semi-definite matrix, with the<br />

diagonal elements all less than or equal to zero. This condition<br />

suggests that the iteration loop above should start with the condition<br />

nzo; furthermore, it generally allows for a unique solution to the<br />

iteration problem.<br />

Summarizing the results for the perfectly observable case, the optimal<br />

feedback control is given by Eq, (2.5.107) where the matrix s is determined<br />

from Eq. (2.5.106A). The Lagrange multiplier matrix A is selected so that<br />

the simultaneous solution of Eq. (2.5.106A) <strong>and</strong> (2.5.111) lead to a control<br />

which satisfies the specified terminal constraints.<br />

2.5.3.2 Perfectly Inobservable Case<br />

The treatment of the, perfectly inobservable case parallels that given<br />

in Section (2.5.2.2) where no terminal conditions were imposed. Again,<br />

the problem is to minimize the performance index<br />

140<br />

(2.5.114)

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