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 neurolinearizer is compared to model predictive recurrent training...

For a class of uncertain nonlinear systems with actuator faults, robust active fault-tolerant control is investigated based on the adaptive observer, feedback linearization, and backstepping design theory. Time-varying faults and bounded uncertainty are simultaneously considered in the paper. An adaptive observer is firstly constructed to estimate the faults and then a backstepping-based active...

using the facts controllers, such as static synchronous compensator (statcom), as it provides continuous reactive power, in the grid including wind turbine (wt) equipped with doubly fed induction generator, for improving voltage profile (under normal circumstances) and providing a transition ability from inductor generator transition state has been proposed. in this paper, in order to control t...

pH control is a challenging problem due to its highly nonlinear nature. In this paper the performances of two different adaptive global linearizing controllers (GLC) are compared. Least squares technique has been used for identifying the titration curve. The first controller is a standard GLC based on material balances of each species. For implementation of this controller a nonlinear state...

This paper proposes a direct adaptive backstepping control scheme for a class of multi-input-multioutput nonlinear uncertain non-affine systems using output recurrent wavelet neural networks (ORWNNs), called DABCORWNN. The proposed ORWNN combines the advantages of wavelet-based neural network, fuzzy neural network (FNN), and output feedback layer. For the tracking of nonlinear non-affine system...

Locally optimal backstepping is extended to output-feedback systemswith input disturbances and nonlinearities that depend only on the measured output. The constructive design blends worst-case "ltering with backstepping, and results in a disturbance attenuating dynamic output-feedback controller that achieves semiglobal inverse optimality and local near-optimality. 2001 Published by Elsevier Sc...

Feedback connection of (strict) passive systems with multiplicative disturbance on the input of one of systems is considered. Series of conditions are proposed, which provide (strict) passivity property for overall system. These conditions enlarge result from Hill, and Moylan (1977), where passivity property of such connection was established. Applications of proposed results to backstepping co...

In this paper, the adaptive fuzzy backstepping output feedback tracking control problem is considered for a class of uncertain stochastic multi-input and multi-output (MIMO) nonlinear systems in pure-feedback form. The stochastic MIMO nonlinear systems under study have unknown nonlinear functions, input saturation and immeasurable states. By using fuzzy logic systems to identify the uncertain n...

In this paper, an adaptive fuzzy robust output feedback control approach is proposed for a class of single input single output (SISO) strict-feedback nonlinear systems without measurements of states. The nonlinear systems addressed in this paper are assumed to possess unstructured uncertainties, unmodeled dynamics and dynamic disturbances, where the unstructured uncertainties are not linearly p...