Search

System nonlinearities, immeasurableness, and uncertainties (especially their coupling/coexistence) have constantly challenged the control design, which requires the controller to be powerful enough to counteract the resulting negative effects. In this paper, a global adaptive output-feedback controller is designed for uncertain nonlinear systems. The proposed controller is of switching type, in which the design parameters are online adjusted on the basis of a switching logic in a recursive manner. This makes the controller powerful enough to compensate the system unknowns and dominate the system nonlinearities and therefore be applicable to a rather wide range of systems. Remarkably, our strategy allows the coexistence of an unknown control direction and unmeasured state--dependent growth but which are substantially excluded in the related literature.An example of the single-link robot arm systemis provided to illustrate the effectiveness of the proposed controller. [ABSTRACT FROM AUTHOR]

Summary: This paper is devoted to the global stabilization via output feedback for a class of nonlinear systems with unknown relative degree, dynamics uncertainties, unknown control direction, and nonparametric uncertain nonlinearities. In particular, the unknown relative degree is without known upper bound, which renders us to research for a filter with varying dimension rather than the ones with over dimensions in the existing literature. In comparison with more popular but a bit stronger input‐to‐state stable or input‐to‐state practically stable requirement, only bounded‐input bounded‐state stable requirement is imposed on the dynamics uncertainties, which affect the systems in a persistent intensity rather than in a decaying one. In this paper, to compensate multiple serious system uncertainties and realize global output‐feedback stabilization, a design scheme via switching logic together with varying dimensional filter is developed. In this scheme, 2 switching sequences, which separately generate the gains of the controller and act as the varying dimensions of the filter, are designed to overcome unknown control direction, dynamics uncertainties and nonparametric uncertain nonlinearities, and unknown relative degree, respectively. A 2‐mass lumped‐parameter structure is provided to show the effectiveness of the proposed method in this paper. [ABSTRACT FROM AUTHOR]