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Motivated by the adaptive control problem for systems with hysteresis, a two-time-scale averaging framework is presented in this paper for systems involving operators, by extending the work of Teel and co-workers. The developed averaging theory is applied to the analysis of a model reference adaptive inverse control scheme for a system consisting of linear dynamics preceded by a Prandtl-Ishlinkskii...
This paper examines an adaptive control scheme for tubular linear motors with micro-metric positioning tolerances. Uncertainties such as friction and other electromagnetic phenomena are approximated with a radial basis function network, which is trained online using a learning law based on Lyapunov design. Differently from related literature, the approximator is trained using a composite adaptation...
In the Immune Neural Network (INN), the key point is stability and convergence. The existing INN has shortages in the control of local optimization, so the paper bring forward INN algorithm which is based on extension theory. With the concepts of dependent function and matter-element, the improved algorithm firstly can optimize architecture and rule extraction of INN. And then, the new algorithm is...
The traditional model reference adaptive system (MRAS) is of parallel configuration. By representing the reference model as an equivalent closed-loop subsystem, these two subsystems can share a controller virtually. An embedded structure of MRAS is thereby presented. In this paper, two approaches are developed for designing the adaptive laws. The adaptive law based on Lyapunov stability theory is...
An adaptive backstepping neural controller design is presented for a class of nonaffine nonlinear system with mismatched uncertainties. By applying backstepping design strategy and online approaching uncertainties with fully tuned radial basis function (RBF) neural networks (NNs), the adaptive tuning rules are derived from the Lyapunov stability theory. A nonlinear tracking differentiator is introduced...
Simulations are given for the anti-rolling effects between fin stabilizer, anti-rolling tank control, and fin/anti-roll tank combined stabilization. Results show that the last design strategy gives much better performance than the two single dynamics strategies (fin or anti-roll tank), and can provide us a full-condition anti-rolling system. The nonlinearity and randomicity of the ship rolling motivates...
This paper provides an alternative approach to solve model reference adaptive control problems of uncertain processes. Plants in this manuscript are described as polytopic LPV systems in fixed polytopes defined by convex hulls of extreme systems, and uncertainties of system parameters correspond to those extreme systems. It is shown that control inputs are composed of weighted sums of control signals...
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