Two classes of partially known systems are considered in this note; both of them have a fractional parameterization of the unknowns. The first class consists of nonlinear systems whose uncertainties are bounded by a function of fractional parameterization, and the second class compromises those systems whose unknown dynamics can directly, but nonlinearly, be parameterized. It is shown that adap...

A class of systems influenced by nonlinearly parameterized perturbations is considered. An estimation scheme is developed whereby exponentially stable estimates of the unknown parameters can be obtained with an arbitrarily large region of attraction, provided the states are available for measurement. The method applies to a class of perturbations with the property that an exponentially stable e...

We consider a class of systems influenced by perturbations that are nonlinearly parameterized by unknown constant parameters, and develop a method for estimating the unknown parameters. The method applies to systems where the states are available for measurement, and perturbations with the property that an exponentially stable estimate of the unknown parameters can be obtained if the whole pert...

Parameter estimation in nonlinear systems is an important issue in measurement, diagnosis and modeling. The goal is to find a differentiator free on-line adaptive estimation algorithm which can estimate the internal unknown parameters of dynamic systems using its inputs and outputs. This thesis provides new algorithms for adaptive estimation and control of nonlinearly parameterized (NLP) system...

In this paper, a new algorithm is described for on-line identification and adaptive control of MIMO affine nonlinear systems having unknown dynamics a priori, by using a nonlinearly parameterized additive recurrent neural network (ARNN). The ARNN uses the radial basis functions (RBF) as activation functions. However, some adjustable parameters (centers and variances) in RBF appear nonlinearly a...

This paper deals with adaptive control of a class of nonlinear systems with a triangular structure and nonlinear parameterization. In Koji' c et al. [(Systems Control Lett. 37 (1999) 267)] it was shown that a class of second-order nonlinearly parameterized systems can be adaptively controlled in a globally stable manner. In this paper, we extend our approach to all nth order systems that have a...

This paper studies global adaptive control of nonlinearly parameterized systems with uncontrollable linearization. Using a new parameter separation technique and the tool of adding a power integrator, we develop a feedback domination design approach for the explicit construction of a smooth adaptive controller that solves the problem of global state regulation. In contrast to the existing resul...

2 Statement of the Problem A large class of problems in parameter estimation concerns systems where parameters occur nonlinearly. In [1]-[5], a stability framework for identification and control of such systems has been established. We address the issue of parameter convergence in such systems in this paper. Sufficient conditions under which parameter estimates converge to their true values are...

This paper presents an adaptive tracking control method for a class of nonlinearly parameterized MIMO dynamic systems with time-varying delay and unknown nonlinear dead-zone inputs. A new high dimensional integral Lyapunov-Krasovskii functional is introduced for the adaptive controller to guarantee global stability of the considered systems and also ensure convergence of the tracking errors to ...