Σύγκριση μεθόδων

	Γραμμικοποίηση μέσω Ανάδρασης	Έλεγχος H-άπειρο
Πεδίο	Θεωρία Ελέγχου	Θεωρία Ελέγχου
Οικογένεια	Machine learning	Machine learning
Έτος προέλευσης	1983	1981
Δημιουργός	Alberto Isidori	George Zames
Τύπος	algorithm	algorithm
Θεμελιώδης πηγή	Isidori, A. (1995). Nonlinear Control Systems (3rd ed.). Springer-Verlag.	Zames, G. (1981). Feedback and optimal sensitivity: Model reference transformations, multiplicative seminorms, and approximate inverses. IEEE Transactions on Automatic Control, 26(2), 301-320.
Εναλλακτικές ονομασίες	Exact Linearization, Nonlinear Feedback Control, Input-Output Linearization	H∞ Control, Robust Control, Minimax Control
Συναφείς	4	4
Σύνοψη	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.	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.