Feedback and Optimal Sensitivity: Model Reference Transformations, Multiplicative Seminorms, and Approximate Inverses

By Tamer Basar. 2001

688 citations recorded by the source corpus.

Subfields: Control and Systems Engineering

View Paper: https://www.semanticscholar.org/paper/7c89526e7a429b44dd610a2da67f80ad47d963a2

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In Control and Systems Engineering

Citations in the corpus

Volatility of Power Grids Under Real-Time Pricing (2011, background): “The limitations of performance and the tradeoffs between performance and robustness are well studies in the context of classical control [11], [12], [13], [14], and have been more recently studied in the context of networked systems (see, e.”
Feedback Systems: An Introduction for Scientists and Engineers (2008, positive): “A major step forward was the development of design methods where robustness was explicitly taken into account, such as the seminal work of Zames [208].”
Feedback controller parameterizations for Reinforcement Learning (2011, background): “In the control literature it is common to enforce robust stability via a small-gain condition by limiting the H∞ norm of the closed-loop transfer function [30], [9], [6].”
Robust output tracking control of SISO plants with multiple operating points and with parametric and unstructured uncertainties (2002, methodology): “Much research has been done on systems with norm-bounded perturbations, and systematic and powerful analysis and design methods have been proposed (Zames 1981, Doyle 1982, Dorato 1987, Francis 1987, Doyle et al. 1989, Dorato and Yedavalli 1990, Doyle et al. 1991, Green and Limebeer 1995, Zhou et…”
Stochastic Inequality Constrained Closed-loop Model Predictive Control: With Application To Chemical Process Operation (2004, background): “This direct approach is known by several names such as the Q-parameterization in control literature, (Zames, 1981), Internal Model Control (IMC) in process control literature, (Garcia and Morari, 1982), but it can be traced back to early analytical feedback design methods, (Newton et al.”
Robust and Optimal Control (2014, background): “In the late 1970s and early 1980s with the pioneering work by Zames [8] and Zames and Francis [9], a theoretic development, now known as the H1 optimal control theory, was taking shape.”
Wiener's Polynomial Chaos for the Analysis and Control of Nonlinear Dynamical Systems with Probabilistic Uncertainties [Historical Perspectives] (2013, background): “Probably one of the main reasons that PCEs were ignored for more than a quarter century by the control community is the community’s early emphasis on systems with worst-case rather than probabilistic uncertainties [69]–[72].”
Disturbance Observer-Based Robust Control and Its Applications: 35th Anniversary Overview (2019, neutral): “parametric control, such as Kharitonov’s theorem [14]–[18].”
On Spectral Learning (2010, background): “The spectral norm, ‖ · ‖∞, is also of interest in the context of filter design (Zames, 1981) in control theory.”
A Characterization of Convex Problems in Decentralized Control$^ast$ (2005, background): “Zames proposed a two-step compensation scheme [30] for strongly stabilizable plants, that is, plants which can be stabilized with a stable compensator.”
Control theory for linear systems (2002, methodology): “The H∞ control problem was originally formulated in the work of Zames, [230].”
Optimal Adaptive Control and Differential Games by Reinforcement Learning Principles (2012, methodology): “In the bounded L2 gain problem (Başar and Olsder, 1999; Van Der Schaft, 1992; Zames, 1981) one desires to find a feedback control policy uðxÞ such that, when xð0Þ 1⁄4 0 and for all disturbances dðtÞ 2 L21⁄20;1Þ one has ðT”
Stochastic H2/H∞ control with (x, u, v)-dependent noise: Finite horizon case (2006, neutral): “INTRODUCTION One of the most important robust control approaches is the so-called H∞ control, which has made great progresses in both theory and practical applications since the foundation work of [1], we refer the reader to [2], [3], [4], [5], [16], [21] and the references therein.”
Control: A perspective (2014, background): “In 1981 George Zames published a paper [700] which laid the foundation for H∞ control.”
Event‐triggered H∞ control for a class of nonlinear networked control systems using novel integral inequalities (2017, background): “The H1 control concept was first proposed by Zames in 1981 [1].”
$ {H}_{ {\infty }}$ Tracking Control of Completely Unknown Continuous-Time Systems via Off-Policy Reinforcement Learning (2015, background): “The H∞ control theory has mostly concentrated on designing regulators to drive the states of the system to zero in the presence of disturbance [1]–[5].”
Robust control design with MATLAB (2005, background): “The pioneering work in the development of the forthcoming theory, now known as the H∞ optimal control theory, was conducted in the early 1980s by Zames [171] and Zames & Francis [172].”