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Delay approach to continuous-discrete observer design for Lipschitz nonlinear systems is discussed. First, the convergence conditions of the nonlinear observer with a linear output correction are established in terms of linear matrix inequalities. In the second part of this note, new matrix conditions are derived to ensure the convergence of the hybrid observer with both linear and nonlinear correction...
This paper studies the global states regulation problem via output feedback for a class of uncertain nonlinear systems and a class of their cascade systems. The uncertain nonlinear perturbed terms of the considered systems are assumed to satisfy a generalized condition which is related to an unknown constant and is more relaxed than the existing triangular-type condition. Due to the presence of unknown...
In this paper, a design method of adaptive output feedback controller for nonlinear systems with higher order relative degree and some uncertainties in control input term is proposed. The controlled systems are rendered the systems with a relative degree of one by introducing two different virtual filters and applying a variable transformation. The actual control input is designed so that the virtual...
In this paper, two robust adaptive control schemes are proposed for a class of uncertain nonlinear systems in a Brunovsky form with unknown dead-zone and sector nonlinearity. The design is based on the principle of sliding mode control and the use of Nussbaum-type function in solving the problem of the completely unknown control gain. The novel description of input nonlinearity which makes the control...
We propose a globally convergent observer for three-state nonlinear systems verifying the uniform complete observability condition. By constructing a time-varying differentiator, we are then able to reproduce the first and the second derivatives of the system output without imposing the boundedness of the states or the output. By exploiting the algebraic observability of the system, we show that the...
This paper investigates the problem of global robust stabilization by state feedback, for a family of high order feedforward (upper-triangular) nonlinear systems with delayed input. The uncertain nonlinearities are assumed to satisfy a polynomial growth assumption with a constant growth rate. The designed controllers, which are continuous but not smooth feedbacks, could achieve global asymptotical...
In this paper we develop a general discrete-time adaptive control approach suitable for nonlinear systems with periodic parametric uncertainties. The underlying idea of the new approach is to convert the periodic parameters into an augmented constant parametric vector by a lifting technique. As such, the well-established discrete-time adaptive control schemes can be easily applied to various control...
A conditional learning control is derived for uncertain nonlinear systems to track repetitive trajectory under the alignment initial condition. The learning process is conditional as it is performed only when the system response is mainly determined by the input. The major advantage of this method over adaptive ILC is that it can handle non-parametric uncertainties. A simulation example is presented...
PID controllers are popular in industrial applications, as they are easy to install and reasonably robust. However, for highly nonlinear systems, the performance of PID controllers can deteriorate quite fast. It is necessary to develop nonlinear PID controllers for controlling nonlinear processes. An approach to design these controllers is to switch between several linear PID controllers using fuzzy...
This paper is concerned with H∞ control problems for a class of uncertain nonlinear systems. In the procedure, neural networks (NNs) are used to model the nonlinear functions, H∞ tracking controller is derived based on Lyapunov function and the notion of dissipativeness. The controller can not only guarantee the stability of the overall control system, but also attenuate the effect of both the external...
The paper is concerned with the robust stability for a nonlinear feedback system with perturbations using robust right coprime factorization method combining with isomorphism approach. The factorization of an unstable plant is realized using the isomorphism approach, and the Bezout identity can be satisfied with the obtained factors and designed operators. As a result, the whole system is overall...
This paper presents a synthesis of fault diagnosis method for nonlinear systems through the parameter estimation using higher order sliding modes. Initially the uncertain parameters of nonlinear system using robust exact differentiator are estimated. Then residual signal is reconstructed using the estimated parameters, inputs, outputs and their estimated derivatives. The novelty of the method is the...
In this paper, operator based internal model control (IMC) of perturbed nonlinear systems is considered. That is, by combining IMC theory and robust right coprime factorization approach, sufficient condition for the designed feedback control systems with perturbation is obtained. Based on the obtained condition, robust stability of the nonlinear systems is obtained. A simulation example is also given...
The problem of stability analysis for two-dimensional (2-D) discrete fuzzy systems is investigated in this paper. The 2-D fuzzy system model is first established based on the Fornasini-Marchesini local state-space (FMLSS) model, and asymptotic stability is derived by means of linear matrix inequality (LMI) technique. The effectiveness of the proposed condition is shown via an example.
This paper is concerned with the variance-constrained controller design problem for a class of uncertain nonlinear stochastic systems with possible actuator faults. The stochastic nonlinearities described by statistical means are quite general that include several well-studied classes of nonlinearities as special cases. A model of actuator failures is adopted which is more practical than the traditional...
In this paper, we proposed a new method of a fuzzy adaptive controller design for a class of non-affine nonlinear systems in which functions of the systems are unknown. The Lyapunov stability of the closed loop system, robustness against uncertainty and external disturbance, the convergence of the output error to zero and the boundedness of the internal signal are guaranteed. An illustrative example...
A fuzzy robust adaptive control design scheme is developed for a class of nonlinear system represented by input-output models with unknown nonlinear function. The control gain of the nonlinear system is unknown. By on-line approximating the unknown nonlinear functions using two Mamdani fuzzy logic systems, the proposed approach does not require the unknown parts to satisfy the linear dependence condition...
This paper presents the solution of the global robust output regulation problem for a class of nonlinear systems with relative degree one without knowing the control direction. The result is also applied to an asymptotic tracking problem associated with the well known Lorenz system.
In this paper, adaptive neural network (NN) control is investigated for a class of block triangular multi-inputmulti-output (MIMO) nonlinear discrete-time systems with each subsystem in pure-feedback form with unknown control directions. Each subsystem is transformed into a predictor form such that the noncausal problem can be avoided in the control design. By exploring the properties of block triangular...
In this paper, a new robust and optimization based nonlinear controller with respect to a certain kind of nonlinear disturbed systems is proposed based on control Lyapunov functions (CLF) concept and receding horizon control (RHC) scheme. This new controller can be divided into two components, one is the robust control law with measurable disturbance information; another is the robust receding horizon...
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