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Then Bismut [13] proved an existence result for optimal controls.
Secondly, we derive the sufficient conditions for optimal controls by building approximating minimizing sequences of functions twice.
Moreover, without ensuring the uniqueness of feasible pairs, we derive a set of sufficient conditions for optimal controls by building approximating minimizing sequences of functions twice.
Finally, we make use of the Pontragin maximum principle and the unique continuation property to obtain the bang-bang property for optimal controls to this problem.
Constructing approximating minimizing sequences of functions twice plays a key role in the proof of looking for optimal controls, which enable us to deal with the multiple solution problem of feasible pairs.
An upper bound is shown to exist on the norm of the slope δ⟨O(T ⟩/δɛ(t) anywhere over the landscape, implying that the control landscape has gentle slopes permitting stable searches for optimal controls.
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We are now in a position to derive the first-order optimality conditions for optimal control problem (3.1 - 3.3 3.1 - 3.3
The main goal of this paper is to derive the optimality conditions for optimal control problem (3.1 - 3.3 3.1 - 3.3
In Section 5 we discuss the formal approach in deriving first-order optimality conditions for optimal control problem (1.1 - 1.4 1.1 - 1.4
In convex optimization techniques for optimal control design, the main challenge is to manage an infinite dimensional Youla parameter.
The properties of these functions are then discussed and optimality conditions for optimal control problem are also given.
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