## Design of Computational Algorithms for Optimal Control by Hilbert Space MethodsDesign of computational algorithms for optical control by Hilbert space methods, and involving cost function. |

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Accessory Problem adjoint function algorithm for Approximation application assume backward basic boundary condition iteration boundary value problem Chapter Choose computational conjugate direction methods consider constant constraints control function control increment convergence cost functional defined Descent Algorithms described determined developed differential equation dynamical system elements equations 35 Example exists expressed first-order forward given gradient Hilbert space initial condition Integrate equation interval inverse inverse mapping involving Jacobian latter less linear linear system matrix minimizing sequence monotone n x n necessary conditions Newton-Raphson nonlinear obtained optimal control problem positive definite procedure provides quadratic Reference Regulator Problem repeat requires respect Riccati equation satisfies second variation algorithm second variation method second-order shown solution solving specified stable steepest descent step Suppose technique terminal Theory update usually