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A METHODOLOGY FOR DESIGNING GUIDANCE AND CONTROL SYSTEMS
AN APPROXIMATE METHOD FOR COMPUTING THE PERFORMANCE
OPTIMUM DESIGN OF INSTRUMENTATION SYSTEMS
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adaptive systems aircraft Appendix applications assume closed-loop configuration closed-loop control combined optimization problem components computed constraints Contract control and estimation control law control schedule cost function cost variation covariance covariance matrix cruise control degrading effect derived deterministic control problem deterministic cost deterministic optimization deviation discussed disturbances and measurement dual variable dynamic programming example given by Eq Guidance and Control instrumentation subsystem law of control mach number matrix measurement adaptive problem measurement control MEASUREMENT NOISE SENSITIVITIES measurement subsystem Meier Menlo Park nominal control nominal trajectory nonlinear obtained open-loop Open-loop control operating cost optimal control optimization theory optimum deterministic optimum law optimum measurement parameter uncertainty performance index perturbation model Peschon plant control probability density functions procedure quadratic cost random variable reduced second-order Sensitivity Equations solution SRI Project Stanford Research Institute stochastic optimization system performance Taylor series techniques tion variation Ax zero