An adaptive robust nonlinear steering controller for ship’s course is developed. Incorporating the Nussbaum-type function gain and adaptive backstepping algorithm, the proposed control strategy requires neither known dynamic parameters of a ship’s model nor any knowledge about environmental disturbances. It is proved that the designed adaptive robust controller of ship steering can guarantee th...

In this paper, adaptive control of a class of nonlinear discrete time dynamical systems with boundedness of all signals is established by using a linear robust adaptive controller and a neural network based nonlinear adaptive controller, and switching between them by a suitably defined switching law. The linear controller, when used alone, assures boundedness of all the signals but not satisfac...

A hybrid adaptive tracking controller for rigid-link flexible-joint (RLFJ) robot manipulators is designed. The controller is hybrid in the sense that an adaptive indirect controller is used to compensate for parametric uncertainties in the rigid-link equation whereas an adaptive robust controller corrects for the dynamics (i.e. mechanical flexibilities) and parametric uncertainty associated wit...

This paper aims to develop robust adaptive fuzzy control techniques to improve tracking performance, where both the tracking error and the modeling error are utilized to adjust system parameters. A hybrid adaptive control scheme including a H∞ compensator is proposed which makes the tracking performance faster and more reliable. Performance analysis is given by using Lyapunov theory. In our pro...

In this paper, the tracking problem for robot manipulators in the presence of unknown friction and modeling uncertainties is considered. A composite tracking control scheme is proposed in which an adaptive friction estimation is used to estimate the extent of friction and a robust controller is then designed to enhance the overall stability and robustness. It is shown that the design of the fri...

This paper presents a robust control scheme for distributed generations (DGs) in islanded mode operation of a microgrid (MG). In this strategy, assuming a dynamic slack bus with constant voltage magnitude and phase angle, nonlinear equations of the MG are solved in the slack-voltage-oriented synchronous reference frame, and the instantaneous active and reactive power reference for the slack bus...

in this paper a new strategy is proposed to design a fixed-structure robust controller for a flexible beam.  robust controller designed by the conventional  loop­ shaping method is not appropriate for a beam because of its high order and complicated form. fixed-structure  loop shaping control in conjunction with particle swarm optimization (pso)algorithm  is used to overcome this drawback. the ...

This paper presents an adaptive nonlinear position controller with velocity constraint, capable of combining the input-output linearization technique and Lyapunov stability theory. Based on the Lyapunov stability theory, the adaptation law of the proposed controller is derived along with the verification of the overall system’s stability. Computer simulation results demonstrate that the propose...

Neural network has good nonlinear function approximation ability. It can be widely used to identify the model of controlled plant. In this chapter, the theories of modeling uncertain plant by using two kinds of neural networks: feed-forward neural network and recurrent neural network are introduced. And two adaptive control strategies for robotic tracking control are developed. One is recurrent...

A fuzzy controller equipped with an adaptive algorithm and two supervisors is developed in this work to achieve tracking performances for a class of uncertain nonlinear single input single output (SISO) systems with external disturbances. The convergence of the training algorithm is guarantied by a gradient projection law. The effect of both the approximation errors and the external disturbance...