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Design and evaluation of a DIY construction system for educational robot kits Vrije Universiteit Brussel Ghent University
Building a robot from scratch in an educational context can be a challenging prospect. While a multitude of projects exist that simplify the electronics and software aspects of a robot, the same cannot be said for construction systems for robotics. In this paper, we present our efforts to create a low-cost do-it-yourself construction system for small robots. We have created three different construction systems (laser-cut screw connectors, ...
A study of integrated experiment design for NMPC applied to the Droop model KU Leuven
Nonlinear model predictive control (NMPC) has become an important tool for optimization based control of many (bio)chemical systems. A requirement for a well performing NMPC implementation is obtaining and maintaining an appropriate mathematical process model. To cope with model degradation in view of plant changes and/or system evolution, developments have been made for linear systems to incorporate the information content of future ...
Simultaneous versus sequential optimal experiment design for the identification of multi-parameter microbial growth kinetics as a function of temperature KU Leuven
Optimal experiment design for parameter estimation (OED/PE) has become a popular tool for efficient and accurate estimation of kinetic model parameters. When the kinetic model under study encloses multiple parameters, different optimization strategies can be constructed. The most straightforward approach is to estimate all parameters simultaneously from one optimal experiment (single OED/PE strategy). However, due to the complexity of the ...
Multi-purpose economic optimal experiment design applied to model based optimal control KU Leuven
© 2016 In contrast to classical experiment design methods, often based on alphabetic criteria, economic optimal experiment design assumes that our ultimate goal is to solve an optimization or optimal control problem. As the system parameters of physical models are in practice always estimated from measurements, they cannot be assumed to be exact. Thus, if we solve the model based optimization problem using the estimated, non-exact parameters, an ...
Guaranteed robust optimal experiment design for nonlinear dynamic systems KU Leuven
This paper is about optimal experiment design for uncertain nonlinear dynamic processes. We are interested in designing experiments which allow to identify the unknown states and parameters of a differential equation from noisy measurements. Here, unpredictable process noise or structural model-plant mismatches can be an additional complication. In this case, robustness aspects have to be taken into account as the experiment has to be planned ...
Robustifying optimal experiment design for nonlinear, dynamic (bio)chemical systems KU Leuven
© 2014 Elsevier Ltd. Dynamic experiments that yield as much information as possible are highly valuable for estimating parameters in nonlinear dynamic processes. Techniques for model-based optimal experiment design enable to systematically design such experiments. However, these experiments depend on the current best estimate of the parameters, which are not necessarily the true values. Consequently, in real experiments (i) the information ...
Robust optimal experiment design for nonlinear dynamic systems* KU Leuven
© 2014 IEEE. Experiments that yield as much information as possible are highly valuable for estimating parameters in nonlinear dynamic processes. Techniques for model based optimal experiment design enable the design of such experiments. However, these experiments depend on the current best estimate of the parameters, which are not necessarily the true values. Consequently, in real experiments (i) the information content can be lower than ...
Optimal experiment design in dynamic bioprocesses: a multi-objective optimisation approach KU Leuven
Dynamic process models can be used for operating, controlling and optimising important bioprocesses, e.g., pharmaceuticals production, enzyme production and brewing. After selecting an appropriate process model structure, parameter estimates have to be obtained based on real-life experiments. To reduce the amount of labour and often cost intensive experiments optimal experiment design (OED) is an indispensable tool. In optimal experiment design, ...
Optimal experiment design for nonlinear dynamic (bio)chemical systems using sequential semidefinite programming KU Leuven
In this paper optimal experiment design for parameter estimation in nonlinear dynamic (bio)chemical processes is studied. To reduce the uncertainty in an experiment a suitable measure of the Fisher information matrix or variance-covariance matrix has to be optimized. In this work, novel optimization algorithms based on sequential semidefinite programming are proposed. The sequential semidefinite programming approach has specific advantages over ...