A robust model reference adaptive control for nonminimum phase systems

DOI10.1007/BF01204922zbMath1001.93042MaRDI QIDQ5957033

Meryem Makoudi, H. Mejhed, Larbi Radouane

Publication date: 15 December 2002

Published in: Circuits, Systems, and Signal Processing (Search for Journal in Brave)

zbMATH Keywords

parameter projectionlow-pass filteradaptive data filteringdirect model reference adaptive controlexponential filterinput-output data modellingleast squares estimation algorithmnon-minimum phase systemssignal normalization

Mathematics Subject Classification ID

Adaptive control/observation systems (93C40) Input-output approaches in control theory (93D25) Adaptive or robust stabilization (93D21)

Cites Work

• Unnamed Item
• Some design guidelines for discrete-time adaptive controllers
• Robust design of adaptive control systems using conic sector theory
• On the robustness of discrete-time indirect adaptive (linear) controllers
• Global boundedness of discrete-time adaptive control just using estimator projection
• Model reference adaptive control with unknown high frequency gain sign
• Approximate identification with closed-loop performance criterion and application to LQG feedback design
• A robust model reference adaptive control for non-minimum phase systems with unknown or time-varying delay
• Identification and control -- Closed-loop issues
• Reference model decomposition in direct adaptive control
• Robustness of continuous-time adaptive control algorithms in the presence of unmodeled dynamics
• Robustness of discrete-time direct adaptive controllers
• Design issues in adaptive control
• Improved least squares identification
• Redesign of explicit and implicit discrete time model reference adaptive control schemes
• Unification of some discrete-time adaptive control schemes
• Robustness of model reference adaptive controllers: an input-output approach
• A stability theorem with applications to adaptive control
• Model reference robust control of a class of SISO systems
• Robust direct adaptive controllers with a new normalization technique
• Improved performance model reference adaptive control with parameter mismatch compensation