手法を比較
選択した手法を並べて確認できます。異なる行はハイライト表示されます。
| 線形二次制御器× | Pontryagin Maximum Principle（ポン ujungin の最大値原理）× | |
|---|---|---|
| 分野 | 制御理論 | 制御理論 |
| 系統 | Machine learning | Machine learning |
| 提唱年≠ | 1960 | 1962 |
| 提唱者≠ | Rudolf Kalman | Lev Pontryagin |
| 種類 | algorithm | algorithm |
| 原典≠ | Kalman, R. E. (1960). Contributions to the theory of optimal control. Boletin de la Sociedad Matematica Mexicana, 5(2), 102-119. link ↗ | Pontryagin, L. S., Boltyanskii, V. G., Gamkrelidze, R. V., & Mischenko, E. F. (1962). The Mathematical Theory of Optimal Processes. John Wiley & Sons. link ↗ |
| 別名≠ | LQR, Linear Quadratic Optimal Control | PMP, Optimal Control, Costate Method |
| 関連≠ | 4 | 3 |
| 概要≠ | The Linear Quadratic Regulator (LQR) is a classical optimal control algorithm that computes a linear feedback law to minimize a quadratic cost function for a linear dynamical system. Introduced by Kalman in 1960, LQR provides a provably optimal, closed-form solution for linear systems and remains fundamental in control theory, robotics, and aerospace applications because of its theoretical elegance and computational efficiency. | The Pontryagin Maximum Principle (PMP) is a fundamental theorem in optimal control theory providing necessary conditions for optimality of a control trajectory. Published by Lev Pontryagin in 1962, PMP generalizes the calculus of variations to control problems with constraints and is the theoretical foundation enabling solution of complex trajectory optimization problems from spacecraft missions to industrial process optimization. |
| ScholarGateデータセット ↗ |
|
|