IMT Institutional Repository: No conditions. Results ordered -Date Deposited. 2024-05-21T19:57:14ZEPrintshttp://eprints.imtlucca.it/images/logowhite.pnghttp://eprints.imtlucca.it/2018-03-12T10:55:17Z2018-03-12T10:55:17Zhttp://eprints.imtlucca.it/id/eprint/4027This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/40272018-03-12T10:55:17ZNonlinear MPC and MHE for Mechanical Multi-Body Systems with Application to Fast Tethered AirplanesMechanical applications often require a high control frequency to cope with fast dynamics. The control frequency of a nonlinear model predictive controller depends strongly on the symbolic complexity of the equations modeling the system. The symbolic complexity of the model equations for multi-body mechanical systems can often be dramatically reduced by using representations based on non-minimal coordinates, which result in index-3 differential-algebraic equations (DAEs). This paper proposes a general procedure to efficiently treat multi-body mechanical systems in the context of MHE & NMPC using non-minimal coordinate representations, and provides the resulting computational times that can be achieved on a tethered airplane system using code generation.Sébastien GrosMario Zanonmario.zanon@imtlucca.itMilan VukovMoritz Diehl2018-03-12T10:52:20Z2018-03-12T10:52:20Zhttp://eprints.imtlucca.it/id/eprint/4024This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/40242018-03-12T10:52:20ZAn Experimental Test Setup for Advanced Estimation and Control of an AirborneWind Energy SystemThis chapter gives a detailed description of a test setup developed at KU Leuven for the launch and recovery of unpropelled tethered airplanes. The airplanes are launched by bringing them up to flying speed while attached by a tether to the end of a rotating arm. In the development of the setup, particular care was taken to allow experimental validation of advanced estimation and control techniques such as moving horizon estimation and model predictive control. A detailed overview of the hardware, sensors and software used on this setup is given in this chapter. The applied estimation and control techniques are outlined in this chapter as well, and an analysis of the closed loop performance is given.Kurt GeebelenMilan VukovMario Zanonmario.zanon@imtlucca.itSébastien GrosAndrew WagnerMoritz DiehlDirk VandepitteJan SweversHammad Ahmad2018-03-12T10:30:32Z2018-03-12T10:30:32Zhttp://eprints.imtlucca.it/id/eprint/4021This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/40212018-03-12T10:30:32ZModel Predictive Control of Autonomous VehiclesThe control of autonomous vehicles is a challenging task that requires advanced control schemes. Nonlinear Model Predictive Control (NMPC) and Moving Horizon Estimation (MHE) are optimization-based control and estimation techniques that are able to deal with highly nonlinear, constrained, unstable and fast dynamic systems. In this chapter, these techniques are detailed, a descriptive nonlinear model is derived and the performance of the proposed control scheme is demonstrated in simulations of an obstacle avoidance scenario on a low-fricion icy road.Mario Zanonmario.zanon@imtlucca.itJanick V. FraschMilan VukovSebastian SagerMoritz Diehl