This paper studies output feedback control of pure-feedback systems with immeasurable states and completely non-affine property. Since availability of all the states is usually impossible in the actual process, we assume that just the system output is measurable and the system states are not available. First, to estimate the immeasurable states a state observer is designed. Relatively fewer res...

In this paper, robust control design is presented for a general class of uncertain non-affine nonlinear systems. The design employs feedback linearization, coupled with two high-gain observers— the first to estimate the feedback linearization error based on the full state information; the second to estimate the unmeasured states of the system when only the system output is available for feedbac...

In this paper, a novel approach for finite-time stabilization of uncertain affine systems is proposed. In the proposed approach, a fast terminal sliding mode (FTSM) controller is designed, based on the input-output feedback linearization of the nonlinear system with considering its internal dynamics. One of the main advantages of the proposed approach is that only the outputs and external state...

A new discretization method for calculating a sampled-data representation of a nonlinear continuous-time system is proposed. The proposed method is based on the wellknown Taylor series expansion and zero-order hold (ZOH) assumption. The mathematical structure of the new discretization method is analyzed. On the basis of this structure, a sampled-data representation of a nonlinear system with a ...

This paper proposes an adaptive backstepping control strategy for a class of uncertain non affine systems using self recurrent neural networks. To assure the stable tracking of nonlinear non affine system, it is first converted to an affine like form and subsequently a wavelet based adaptive backstepping controller is developed. Self recurrent wavelet neural network (SRWNN) is used to approxima...

In this paper, we consider nonlinear affine-incontrol systems and present the L1 adaptive controller for the case when the performance specifications are defined via a nonlinear system of similar structure. The L1 adaptive controller ensures that the nonlinear, affine-in-control, uncertain system follows its ideal model during the transient and steadystate, if the adaptation gain is selected su...

This paper introduces a new decentralized adaptive neural network controller for a class of large-scale nonlinear systems with unknown non-affine subsystems and unknown interconnections represented by nonlinear functions. A multilayer feedforward neural network is used to represent the controller’s structure. The ultimate boundedness of the closed loop system is guaranteed through Lyapunov stab...