Abstract
Optimal control is one particular branch of modern control. It deals with the problem of finding a control law for a given system such that a certain optimality criterion is achieved. A control problem includes a cost functional that is a function of state and control variables. An optimal control is a set of differential equations describing the paths of the control variables that minimize the cost function. The optimal control can be derived using Pontryagin’s maximum principle (a necessary condition also known as Pontryagin’s minimum principle or simply Pontryagin’s Principle), or by solving the Hamilton–Jacobi–Bellman (HJB) equation (a sufficient condition). For linear systems with quadratic performance function, the HJB equation reduces to the algebraic Riccati equation(ARE) (Zhang et al, Adaptive dynamic programming for control-algorithms and stability. Springer, London, 2013, [1]).
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Song, R., Wei, Q., Li, Q. (2019). Introduction. In: Adaptive Dynamic Programming: Single and Multiple Controllers. Studies in Systems, Decision and Control, vol 166. Springer, Singapore. https://doi.org/10.1007/978-981-13-1712-5_1
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DOI: https://doi.org/10.1007/978-981-13-1712-5_1
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