Dynamic Optimization"Dynamic Optimization" takes an applied approach to its subject, offering many examples and solved problems that draw from aerospace, robotics, and mechanics. The abundance of thoroughly tested general algorithms and Matlab codes provide the reader with the practice necessary to master this inherently difficult subject, while the realistic engineering problems and examples keep the material interesting and relevant. FEATURES/BENEFITS
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41 pages matching Backward Shooting in this book
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1 POPParameter Optimization Using Gradient | 30 |
2 POPNParameter Optimization Using NR | 41 |
Dynamic Optimization | 45 |
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altitude analytical angle backward sequencing Backward Shooting boundary conditions calculate calculus of variations climb Compare your results Compute constant CONSTR control histories determined discrete Discrete Optimization DOPC DTDP dual problem DVDP for Max Dynamic Optimization eigenvalues eigenvectors eqns Example feedback gains FMINU FOPC FOPT FSOLVE in MATLAB ft/sec given H₁ initial guess integration iterations Lagrange multipliers linear listed in Table MATLAB Code Max Range minimize mxit necessary conditions normalized numerical optimal control optimal path optn parameter performance index phugoid plot the optimal Range with Gravity results with Figure Riccati equation Script Shooting Algorithm Show Solar Sail solved specified stationary point subroutine tangent law terminal constraints terminal error time-to-go TPBVP units variable vector velocity version of Problem wish to find x(tƒ zero