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安宇熙 陸軍士官學校 1980 한국군사학논집 Vol.20 No.-
The optimal stochastic linear sampled-data control problem is formulated, the existence of an optimal solution is proved, and an algorithm for computing the optimal control is developed. The cost functional used measures both control performance and the cost of implementing and operating a sampled-data controller. The constraints, improved by the sampling criterion, can specify or constrain the length of eacn sampling interval. Thus a periodic or aperiodic sampling criterion can result which is either optimal or specified apriori. The optimal sampling criterion is shown to depend on the control law; the system dynamics; the statistics of the system distribution, measurement noise and initial state; the performance index; and the sampling constraints.
安宇熙 陸軍士官學校 1981 한국군사학논집 Vol.21 No.-
The development of an optimal Sampling theory is proposed with three optimal sampling processes. Optimal aperiodic, optimal adaptive, and optimal predictive sampling Criteria are formulated based on whether the signal model is available, whether signal measurements are available, and whether on-line computation-adaptation of the sampling process is required. These optimal Processes are used for both adaptive compensation of control systems and interference rejection in radar, sonar, loran, and communication systems. Costs of implementations are developed and are included in the performance indices. Computational algorithms are developed and comparisons of performance and sampling efficiency are made for various optimal sampling criteria. Finally, a methodology for formulating and for designing optimal sampling processes is developed.