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Autonomous Learning Talk Prof. William W. Hager 28-06-2018 Discrete approximations in optimal control: From Runge Kutta to Pseudospectral Methods Optimal control problems are often too complex to solve analytically. Computational methods usually replace the continuous infinite dimensional problem by a finite dimensional discrete approximation. The talk will survey classical discretization techniques based on a Runge-Kutta approximation to the differential equations (an h-method) and then introduce recent approximations based on collocation at the roots of orthogonal polynomials (a p-method). The best approximations are often achieved using an hp-framework that combines the best features of both approaches. Numerical results using t... Jia-Jie Zhu
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