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| Control H-infinit (H∞)× | Linealització per retroalimentació× | |
|---|---|---|
| Camp | Teoria de control | Teoria de control |
| Família | Machine learning | Machine learning |
| Any d'origen≠ | 1981 | 1983 |
| Autor original≠ | George Zames | Alberto Isidori |
| Tipus | algorithm | algorithm |
| Font seminal≠ | Zames, G. (1981). Feedback and optimal sensitivity: Model reference transformations, multiplicative seminorms, and approximate inverses. IEEE Transactions on Automatic Control, 26(2), 301-320. DOI ↗ | Isidori, A. (1995). Nonlinear Control Systems (3rd ed.). Springer-Verlag. DOI ↗ |
| Àlies | H∞ Control, Robust Control, Minimax Control | Exact Linearization, Nonlinear Feedback Control, Input-Output Linearization |
| Relacionats | 4 | 4 |
| Resum≠ | H-infinity (H∞) control is a robust control method that minimizes the worst-case gain from disturbances to controlled outputs, formulated as a minimax optimization problem. Pioneered by Zames in the early 1980s, H∞ control provides a principled way to design feedback controllers that tolerate model uncertainty, unmodeled dynamics, and disturbances while maintaining stability and performance, making it essential for applications requiring guaranteed robustness. | Feedback Linearization is a nonlinear control technique that uses a nonlinear state-feedback transformation to convert a nonlinear system into a linear one, enabling the use of standard linear control methods. Developed by Isidori, Sontag, and others in the 1980s, feedback linearization is conceptually elegant and powerful: if the system satisfies certain structural conditions (relative degree, decoupling matrix rank), the nonlinearities can be exactly cancelled through feedback, reducing the problem to linear design. |
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