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This study focuses in the output feedback stabilisation of constrained linear systems affected by uncertainties and noisy output measurements. The system states are restricted inside a given polytope and a classical Luenberger observer is used to reconstruct the unmeasurable states from output observations. Based on the observed states, a state feedback is proposed as the control input. The stability analysis and the control design are done using an extended version of the attractive ellipsoid method (AEM) approach. To avoid the violation of state constraints, this work proposes a barrier Lyapunov function (BLF) based analysis. The control parameters are obtained throughout the solution of some optimisation problems such that the BLF ensures an approximation of the constraints by a maximal ellipsoidal set and the AEM provides the characterisation of a minimal ultimately bounded set for the closed-loop system solutions. Numerical simulations show the advantages using the BFL-AEM methodology against classical sub-optimal controllers in academic second order and third order examples. Then, the proposed control strategy is applied over a Buck DC-DC converter. In all the cases, the method proposed here prevails over the other controllers. [ABSTRACT FROM AUTHOR]

This article solves the tracking trajectory problem of teleoperated robotic systems with different workspaces. The overall robotic system satisfies a regular master–slave structure with a delta-robot as the master device and a planar manipulator attached to a Cartesian robot with five degrees of freedom (DOFs) as the slave device. A forward kinematics analysis describes the workspace for the delta-robot and the five-DOFs manipulator. A coordinate transformation based on sigmoidal functions establishes the relation between the workspaces for both robotic devices. The obtained transformation yields a feasible workspace for the slave robot. Then, an inverse kinematics analysis provides the desired reference trajectories. The tracking trajectory control implements a robust strategy based on Barrier Lyapunov functions. The barrier controller does not allow the slave robot to reach non-attainable configurations. State-dependent gains characterized the obtained controller taking into account the different workspaces for each device. Numerical results describe the suggested controller applied in a virtual teleoperated robot and a real robotic system platform. The obtained results confirm the improvements (measured in terms of the mean square error and the l 2 norm of the applied controls) of the proposed controller against a traditional state feedback realization. Furthermore, the results show that the trajectories of the slave robot do not leave the valid workspace. • Output feedback control for teleoperated manipulators under state constraints. • Adaptive control formulation based on logarithmic barrier Lyapunov functions. • Super-twisting differentiator implementation to obtain the tracking error derivative. • Experimental evaluations on a manipulator (slave) and a Delta robot (master). [ABSTRACT FROM AUTHOR]