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We aim to design in the present paper an adaptive output feedback control scheme to address the tracking problem of an uncertain system having full relative degree in the presence of neglected dynamics and modelling errors. Then, the obtained controller is augmented by an online radial basis function neural network (RBF NN) that is used to adaptively compensate for the nonlinearity existing in the...
This paper presents adaptive neural tracking control for a class of uncertain single-input single-output (SISO) non-affine nonlinear systems in general form. To deal with the non-affine appearance of the control variables, the Taylor series expansion is employed to transform the systems into a block-triangular affine form in the neighborhood of the ideal unknown control law. The developed neural control...
In this paper an adaptive control technique combined with the so-called IDA-PBC (Interconnexion Damping Assignment, Passivity Based Control) controller is proposed for the stabilization of a class of underactuated mechanical systems, namely, the Inertia Wheel Inverted Pendulum (IWIP). It has two degrees of freedom with one actuator. The IDA-PBC stabilizes for all initial conditions (except a set of...
The main objective of this work is to study design methods of polynomial control laws by pole placement that presents actually smart solutions to many industrial applications. Even if these regulators are widely used, most of their applications concern problems where the reference signal does not vary in time. In this paper, we propose an indirect adaptive controller by fractional order pole placement,...
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