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This paper considers the global output-feedback stabilisation for power integrator systems with unknown control direction. The presence of uncontrollable and unobservable linearisation renders the strategy based on Nussbaum function rather difficult (even impossible) to compensate the unknown control direction. In this paper, to dominate the inherent nonlinearities and unknowns, a powerful switching strategy is proposed by combining an output-feedback scheme and a switching mechanism. First, a special case with known control direction is considered to provide a basic structure and selection rules of design parameters for the expected controller, and then, the essential case with unknown control direction is investigated to build a suitable switching logic to online tune the design parameters. The proposed switching-type output-feedback controller guarantees that all the system signals are globally bounded and ultimately converge to zero. A numerical example is given to illustrate the effectiveness of the proposed methods. [ABSTRACT FROM AUTHOR]

This paper addresses the global adaptive stabilisation via switching and learning strategies for a class of uncertain nonlinear systems. Remarkably, the systems in question simultaneously have unknown control directions, unknown input disturbance and unknown growth rate, which makes the problem in question challenging to solve and essentially different from those in the existing literature. To solve the problem, an adaptive scheme via switching and learning is proposed by skilfully integrating the techniques of backstepping design, adaptive learning and adaptive switching. One key point in the design scheme is the introduction of the learning mechanism, in order to compensate the unknown input disturbance, and the other one is the design of the switching mechanism, through tuning the design parameters online to deal with the unknown control directions, unknown bound and period of input disturbance and unknown growth rate. The designed controller guarantees that all the signals of the resulting closed-loop systems are bounded, and furthermore, the closed-loop system states globally converge to zero. [ABSTRACT FROM AUTHOR]