High-performance motion control applications require precise tracking of rapidly changing speed/position and flux trajectories. In this short paper, we present an energy-shaping controller and an input-output linearization controller for current-fed induction motors. Induction motor can be represented as the negative feedback interconnection of passive electrical and mechanical subsystems [1, 2...

In this paper, a mixed robust feedback linearization with linear GH∞ controller is applied to a nonlinear quadrotor unmanned aerial vehicle. An actuator saturation and constrain on state space output are introduced to analyse the worst case of control law design.The results show that the overall system becomes robust when weighting functions are chosen judiciously. Performance issues of the con...

We show that an adaptive input/output feedback linearization control scheme for minimum phase nonlinear systems is robust with respect to unstructured plant uncertainties that include such as unmodeled dynamics and disturbances, provided the adaptive law is modiied in the same fashion as for linear systems, and the plant nonlinearities satisses some growth constraints. In the analysis we utiliz...

Resumo: This paper presents a nonlinear controller for uncertain single-input–single-output nonlinear systems (SISO). The adopted approach is based on the feedback linearization strategy and enhanced by a fuzzy inference algorithm to cope with modeling inaccuracies and external disturbances that can arise. An application of this nonlinear controller to a second-order nonlinear system is also pr...

Abstract: In this paper, the controller introduced represent, at the best knowledge of the authors, the first application of feedback linearization technique to control a Twin Rotor Multi-input Multi-output System (TRMS). With the coupling effects considered as the uncertainties, the highly coupled nonlinear TRMS is decomposed into a horizontal and a vertical subsystem. Then, two control laws a...

In this article, the innuence of uncertainty on weights and biases of neural networks on the input/output behavior is investigated. Moreover, a uncertainty description of uncertain neural networks is derived and an appropriate norm bound of the model uncertainty , which is needed for robust control design, is derived. Finally, feedback linearization is used in order to fully incorporate neural ...

 An adaptive input-output linearization method for general nonlinear systems is developed without using states of the system. Another key feature of this structure is the fact that, it does not need model of the system. In this scheme, neurolinearizer has few weights, so it is practical in adaptive situations.  Online training of neuroline...

This article addresses the robust output regulation problem for a class of nonlinear switched power converters after its linearization by means of a change of the control vector variable. The methodology employs a dynamic state feedback control law and considers parametric uncertainty due to unknown values of resistive loads. Restrictions arising from the fact that the control gains exhibit fix...

Abstract – This paper describes a novel structure for single phase Unified Power Quality Conditioner-Distributed Generation (UPQC-DG) with direct grid connected DC-AC converter for low DC output DG systems which can be used not only for compensation of power quality problems but also for supplying of load power partly. This converter has been composed of one full-bridge inverter, one three wind...