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This paper addresses the problem of velocity tracking control for various fully-actuated robotic vehicles. The presented method, which is based on transformation of equations of motion allows one to use, in the control gain matrix, the dynamical couplings existing in the system. Consequently, the dynamics of the vehicle is incorporated into the control process what leads to fast velocity error convergence. The stability of the system under the controller is derived based on Lyapunov argument. Moreover, the robustness of the proposed controller is shown too. The general approach is valid for 6 DOF models as well as other reduced models of vehicles. Simulation results on a 6 DOF indoor airship validate the described velocity tracking methodology.
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Some recent works have established the importance of handling abundant reference information in multi-criteria sorting problems. More valid information allows a better characterization of the agent’s assignment policy, which can lead to an improved decision support. However, sometimes information for enhancing the reference set may be not available, or may be too expensive. This paper explores an automatic mode of enhancing the reference set in the framework of the THESEUS multi-criteria sorting method. Some performance measures are defined in order to test results of the enhancement. Several theoretical arguments and practical experiments are provided here, supporting a basic advantage of the automatic enhancement: a reduction of the vagueness measure that improves the THESEUS accuracy, without additional efforts from the decision agent. The experiments suggest that the errors coming from inadequate automatic assignments can be kept at a manageable level.
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