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ONLINELEARNING CONTROL SYSTEMS
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20 arcsec adaptive computer adaptive control admissible region Appendix application artificial intelligence assumed attitude control attitude errors augmented plant parameter Automatic Control closed-loop components control choice control gains control situation covariances depicted in fig discussed disturbance torques Douglas Report elements environment equations estimation errors Experiment feedback gains feedback parameter vector Figure filter function goal circuit hence hypercubes initial input patterns iteration Kalman filter lb-ft Learning Control Systems Learning Machines learning network Learning Systems limit cycle linear Lyapunov functions matrix nominal control situations observed obtained on-line-learning control system on-line-optimal feedback parameter optimal control output overall Paper presented pattern recognition performance index plant parameter space priori problem Purdue University random random-optimization reinforcement Section Self-Organizing Control Systems self-organizing system shown in fig simulations specific stochastic approximations Stochastic Automata subgoal system in fig Table techniques threshold time-optimal control time-varying training sample values Wright-Patterson AFB xj(t