Adaptive Control: Actual Status and Trends

Important progress in research and application of Adaptive Control Systems has been achieved in the last ten years. The techniques which are currently used in applications will be reviewed. Theoretical aspects currently under investigation and which are related to the application of adaptive control techniques in various fields will be briefly discussed. Applications in various areas will be briefly reviewed. The use of adaptive techniques for vibrations monitoring and active vibration control will be emphasized

Robustness of continuous-time adaptive control algorithms in the presence of unmodeled dynamics

"April 1983"Bibliography: p. 26-27."NASA/NGL-22-009-124" "ONR/N00014-82-K-0582 (NR 606-003) "NSF/ECS-8210960"Charles E. Rohrs, Lena Valavani, Michael Athans, Gunter Stein

State-of-the-art in aerodynamic shape optimisation methods

Aerodynamic optimisation has become an indispensable component for any aerodynamic design over the past 60 years, with applications to aircraft, cars, trains, bridges, wind turbines, internal pipe flows, and cavities, among others, and is thus relevant in many facets of technology. With advancements in computational power, automated design optimisation procedures have become more competent, however, there is an ambiguity and bias throughout the literature with regards to relative performance of optimisation architectures and employed algorithms. This paper provides a well-balanced critical review of the dominant optimisation approaches that have been integrated with aerodynamic theory for the purpose of shape optimisation. A total of 229 papers, published in more than 120 journals and conference proceedings, have been classified into 6 different optimisation algorithm approaches. The material cited includes some of the most well-established authors and publications in the field of aerodynamic optimisation. This paper aims to eliminate bias toward certain algorithms by analysing the limitations, drawbacks, and the benefits of the most utilised optimisation approaches. This review provides comprehensive but straightforward insight for non-specialists and reference detailing the current state for specialist practitioners

Stable Adaptive Control Using New Critic Designs

Classical adaptive control proves total-system stability for control of linear plants, but only for plants meeting very restrictive assumptions. Approximate Dynamic Programming (ADP) has the potential, in principle, to ensure stability without such tight restrictions. It also offers nonlinear and neural extensions for optimal control, with empirically supported links to what is seen in the brain. However, the relevant ADP methods in use today -- TD, HDP, DHP, GDHP -- and the Galerkin-based versions of these all have serious limitations when used here as parallel distributed real-time learning systems; either they do not possess quadratic unconditional stability (to be defined) or they lead to incorrect results in the stochastic case. (ADAC or Q-learning designs do not help.) After explaining these conclusions, this paper describes new ADP designs which overcome these limitations. It also addresses the Generalized Moving Target problem, a common family of static optimization problems, and describes a way to stabilize large-scale economic equilibrium models, such as the old long-term energy model of DOE.Comment: Includes general reviews of alternative control technologies and reinforcement learning. 4 figs, >70p., >200 eqs. Implementation details, stability analysis. Included in 9/24/98 patent disclosure. pdf version uploaded 2012, based on direct conversion of the original word/html file, because of issues of format compatabilit