Titlebook: Mechanics and Control; Proceedings of the 4 Janislaw M. Skowronski,Henryk Flashner,Ramesh S. G Conference proceedings 1992 Springer-Verlag

growth-factor

Parametric robust control by quantitative feedback theory, issue of engineering significance in many design applications. Quantitative feedback theory (QFT) is very effective for dealing with this class of problems even when there exist hard constraints on closed loop response. In this paper, SISO-QFT is viewed formally as a sensitivity constrained multi o

FIG

On robustness of systems with structured uncertainties, direct method has been often utilized to determine the bounds for nonlinear, time-dependent functions p. which can be tolerated by a stable nominal system. In most cases quadratic forms are used either as components of vector Lyapunov function or as a function itself. The resulting estimates are us

DEFT

Discrete adaptive algorithms and neural network controllers for nonlinear dynamics, derive an adaptive class of stabilizing controllers via Liapunov direct method and compare them with the control obtained through the design of a suitable neural network. Similarities and differences and advantages/defficiencies of both approaches are shown, but at this stage analysis is mainly the

Rejuvenate

amygdala

Mutual reference adaptive control of nonlinear uncertain systems,ding each other in a specified sense, subject to bounded uncertainty of their parameters (MURAC). The error equation approach classical in MRAC is replaced by a different approach which may be called the product-state-space method. Signal adaptive feedback controllers and adaptive laws are proposed

得意人

Adaptive identification and model tracking by a flexible spacecraft, by a hybrid multidimensional system with high (untruncated) geometric nonlinearity and Coriolis forces. It is to be controlled adaptively to track a rigid body reference model with desired dynamics. To this aim the system is replaced by a nonlinear adaptive, state and parameter identifier with cons

鬼魂

Observers for controllers with matched uncertainty in A, B and C matrices,s, is assumed to satisfy certain matching conditions. Lyapunov techniques are used to establish sufficient condition for stability for a given uncertainty bound. In particular, sufficient conditions are obtained that, if met, guarantee stabilization regardless of the size of the uncertainty.

Liability

Discrete adaptive algorithms and neural network controllers for nonlinear dynamics, derive an adaptive class of stabilizing controllers via Liapunov direct method and compare them with the control obtained through the design of a suitable neural network. Similarities and differences and advantages/defficiencies of both approaches are shown, but at this stage analysis is mainly theoretical.

滔滔不绝地说

Conference proceedings 1992d uncertain mechanical sy-tems and promoting application of advanced mechanics in con-trol. The fourth meeting continues the tradition with 17papers containing original and recent work of the partici-pants developed in 3 basic directions: feed-back control ofuncertain systems,flexible mechanical structures and flightcontrol.

催眠药