Journal ArticleDOI
Nonlinear network structures for feedback control
TLDR
A framework is given for controller design using Nonlinear Network Structures, which include both neural networks and fuzzy logic systems, and extensions are discussed to force control, backstepping control, and output feedback control, where dynamic nonlinear nets are required.Abstract:
A framework is given for controller design using Nonlinear Network Structures, which include both neural networks and fuzzy logic systems. These structures possess a universal approximation property that allows them to be used in feedback control of unknown systems without requirements for linearity in the system parameters or finding a regression matrix. Nonlinear nets can be linear or nonlinear in the tunable weight parameters. In the latter case weight tuning algorithms are not straightforward to obtain. Feedback control topologies and weight tuning algorithms are given here that guarantee closed-loop stability and bounded weights. Extensions are discussed to force control, backstepping control, and output feedback control, where dynamic nonlinear nets are required.read more
Citations
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Journal ArticleDOI
Adaptive output feedback control of nonlinear systems using neural networks
TL;DR: A direct adaptive output feedback control design procedure is developed for highly uncertain nonlinear systems, that does not rely on state estimation, and extends the universal function approximation property of linearly parameterized neural networks to model unknown system dynamics from input/output data.
Journal ArticleDOI
Adaptive Trajectory Control for Autonomous Helicopters
Eric N. Johnson,Suresh K. Kannan +1 more
TL;DR: In this paper, pseudocontrol hedging (PCH) was used to protect the adaptation process from actuator limits and dynamics, thus, minimizing the effects of model error in all six degrees of freedom and leading to more accurate position tracking.
Proceedings ArticleDOI
Concurrent learning for convergence in adaptive control without persistency of excitation
Girish Chowdhary,Eric N. Johnson +1 more
TL;DR: It is shown that for an adaptive controller that uses recorded and instantaneous data concurrently for adaptation, a verifiable condition on linear independence of the recorded data is sufficient to guarantee exponential tracking error and parameter error convergence.
Journal ArticleDOI
Asymptotic Tracking for Uncertain Dynamic Systems Via a Multilayer Neural Network Feedforward and RISE Feedback Control Structure
TL;DR: How a recently developed continuous robust integral of the sign of the error (RISE) feedback term can be incorporated with a NN-based feedforward term to achieve semi-global asymptotic tracking is described.
Journal ArticleDOI
Limited authority adaptive flight control for reusable launch vehicles
TL;DR: In this article, a method is introduced that allows an adaptive law to be designed for the system without these input characteristics and then to be applied to the system with these characteristics, without affecting adaptation.
References
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Journal ArticleDOI
Multilayer feedforward networks are universal approximators
TL;DR: It is rigorously established that standard multilayer feedforward networks with as few as one hidden layer using arbitrary squashing functions are capable of approximating any Borel measurable function from one finite dimensional space to another to any desired degree of accuracy, provided sufficiently many hidden units are available.
Book
Applied Nonlinear Control
TL;DR: Covers in a progressive fashion a number of analysis tools and design techniques directly applicable to nonlinear control problems in high performance systems (in aerospace, robotics and automotive areas).
Book
Adaptive Control
TL;DR: Benefiting from the feedback of users who are familiar with the first edition, the material has been reorganized and rewritten, giving a more balanced and teachable presentation of fundamentals and applications.
Book
Adaptive filtering prediction and control
Graham C. Goodwin,Kwai Sang Sin +1 more
TL;DR: This unified survey focuses on linear discrete-time systems and explores the natural extensions to nonlinear systems and summarizes the theoretical and practical aspects of a large class of adaptive algorithms.
Book
Robot dynamics and control
TL;DR: This self-contained introduction to practical robot kinematics and dynamics includes a comprehensive treatment of robot control, providing background material on terminology and linear transformations and examples illustrating all aspects of the theory and problems.