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This paper proposes an iterative method for solving non-convex optimization problems which we call sequential convex programming (SCP) and an application of our method to time trajectory planning problem for a car motion. Firstly, we introduce a formulation of the motion of a car along a reference trajectory as an optimal control problem. We use a special convexity based formulation path employing...
Traditional input shaping filters are linear mappings between the reference input and the system input. These filters are often unnecessarily conservative with respect to input and output bounds if multiple references with different amplitudes are applied. This conservatism is due to the off-line computation of the prefilter. This paper presents an on-line input prefilter design approach to overcome...
This paper illustrates the capabilities of model predictive control for the control of automotive powertrains. We consider the minimization of the fuel consumption of a gasoline engine through dynamic optimization. The minimization uses a mean value model of the powertrain and vehicle. This model has two state variables: the pressure in the engine manifold and the engine speed. The control input is...
Building on previous propositions to generate walking gaits online through the use of linear model predictive control, the goal of this paper is to show that it is possible to allow on top of that a continuous adaptation of the positions of the foot steps, allowing the generation of stable walking gaits even in the presence of strong perturbations, and that this additional adaptation requires only...
Aim of this study is to compare two variants of the real-time iteration (RTI) scheme in nonlinear model predictive control (NMPC): the standard RTI scheme as described in M. Deihl (2001) and a new adjoint based RTI scheme as described in H. G. Bock et al. (2004) and L. Wirsching (2006). The authors compare their performance on returning a chain of spring connected masses to its steady state, after...
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