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Research on sub-optimal Model Predictive Control (MPC) has led to a variety of optimization methods based on explicit or online approaches, or combinations thereof. Its foremost aim is to guarantee essential controller properties, i.e. recursive feasibilit ...
Solving optimal control problems for many different scenarios obtained by varying a set of parameters in the state system is a computationally extensive task. In this paper we present a new reduced framework for the formulation, the analysis and the numeri ...
The aim of this work is to develop a controllable synthesis pathway which produces a stable alumina layer on the surface of carbon nanotubes by impregnation method. Precursor compounds such as aluminium isopropoxide and aluminium-acetylacetonate were used ...
The topic of this thesis is the study of several stochastic control problems motivated by sailing races. The goal is to minimize the travel time between two locations, by selecting the fastest route in face of randomly changing weather conditions, such as ...
This paper looks at the efficiency of the parame- terisation of the degrees of freedom within an optimal predictive control algorithm. It is shown that the conventional approach of directly determining each individual future control move is not efficient i ...
This paper deals with the finite horizon stochastic optimal control problem with the expectation of the 1-norm as the objective function and jointly Gaussian, although not necessarily independent, disturbances. We develop an approximation strategy that sol ...
This master thesis aims at the development, analysis and computer implementation of effcient numerical methods for the solution of optimal control problems based on parametrized partial differential equations. Our goal isfto develop a new approach based on ...
This paper proposes a feedback law capable of swinging up and stabilizing the cartpendulum system. The approach uses an iterative algorithm that is typically used to construct a locally linearizing output for nonlinear control-affine systems. However, rath ...
We propose a dynamic optimization approach to calculate optimal feedforward controls for exact path-following problems of differentially flat systems. Besides the derivation of a small dimensional optimal control problem, we provide easily checkable condit ...
This study aims at providing a control-learning framework capable of generating optimal locomotion patterns for the modular robots. The key ideas are firstly to provide a generic control structure that can be well-adapted for the different morphologies and ...
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