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Evans, Michael (author), Tindemans, S.H. (author), Angeli, David (author)
We consider the problem of dispatching a fleet of heterogeneous energy storage units to provide grid support. Under the restriction that recharging is not possible during the time frame of interest, we develop an aggregate measure of fleet flexibility with an intuitive graphical interpretation. This analytical expression summarises the full set...
journal article 2020
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Evans, Michael (author), Angeli, David (author), Strbac, Goran (author), Tindemans, S.H. (author)
We present a method to find the maximum magnitude of any supply-shortfall service that an aggregator of energy storage devices is able to sell to a grid operator. This is first demonstrated in deterministic settings, then applied to scenarios in which device availabilities are stochastic. In this case we implement chance constraints on the...
conference paper 2019
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Alibekov, Eduard (author), Kubalík, Jiří (author), Babuska, R. (author)
Approximate Reinforcement Learning (RL) is a method to solve sequential decisionmaking and dynamic control problems in an optimal way. This paper addresses RL for continuous state spaces which derive the control policy by using an approximate value function (V-function). The standard approach to derive a policy through the V-function is...
journal article 2019
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Evans, Michael P. (author), Tindemans, S.H. (author), Angeli, David (author)
This paper considers the optimal dispatch of energy-constrained heterogeneous storage units to maximise securityof supply. A policy, requiring no knowledge of the future, ispresented and shown to minimise unserved energy during supply-shortfall events, regardless of the supply and demand profiles.It is accompanied by a graphical means to rapidly...
journal article 2019
document
de Groot, T.H. (author), Krasnov, O.A. (author), Yarovoy, Alexander (author)
Modern sensors, such as multifunctional radars, comprise many settings and the number of controllable settings is increasing due to technological advance. Although having many settings allows many capabilities, it simultaneously requires an automatic manager to control them. This paper proposes mission-driven resource management to control...
journal article 2018
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Kuppens, P.R. (author), Wolfslag, W.J. (author)
Robots would perform better when their mechanical structure is specifically designed for their designated task, for instance by adding spring mechanisms. However, designing such mechanisms, which match the dynamics of the robot with the task, is hard and time consuming. To assist designers, a platform that automatically designs dynamical...
journal article 2018
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Kudruss, Manuel (author), Koryakovskiy, I. (author), Vallery, H. (author), Mombaur, Katja (author), Kirches, Christian (author)
Today’s humanoid robots are complex mechanical systems with many degrees of freedom that are built to achieve locomotion skills comparable to humans. In order to synthesize whole-body motions, real-tme capable direct methods of optimal control are a subject of contemporary research. To this end, Nonlinear Model Predictive Control is the method...
report 2018
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De Jong, Jenny (author), Fokkink, R.J. (author), Olsder, G.J. (author), Schwab, A.L. (author)
In a cycling time trial, the rider needs to distribute his power output optimally to minimize the time between start and finish. Mathematically, this is an optimal control problem. Even for a straight and flat course, its solution is non-trivial and<br/>involves a singular control, which corresponds to a power that is slightly above the aerobic...
journal article 2017
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Ghosh, D. (author), Baldi, S. (author)
Several classes of multi-model adaptive control schemes have been proposed in literature: instead of one single parameter-varying controller, in this adaptive methodology multiple fixed-parameter controllers for different operating regimes (i.e. different models) are utilised. Despite advances in multi-model adaptive control theory, the question...
journal article 2017
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Kubalík, Jiří (author), Alibekov, Eduard (author), Babuska, R. (author)
Model-based reinforcement learning (RL) algorithms can be used to derive optimal control laws for nonlinear dynamic systems. With continuous-valued state and input variables, RL algorithms have to rely on function approximators to represent the value function and policy mappings. This paper addresses the problem of finding a smooth policy...
journal article 2017
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Dufour, R. (author), De Meulenaere, J. (author), Elham, A. (author)
This paper presents the multidisciplinary optimization of an aircraft carried sub-orbital spaceplane. The optimization process focused on three disciplines: the aerodynamics, the structure and the trajectory. The optimization of the spaceplane geometry was coupled with the optimization of its trajectory. The structural weight was estimated using...
journal article 2015
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Shu, Y. (author), Daamen, W. (author), Ligteringen, H. (author), Hoogendoorn, S.P. (author)
Due to the ever-increasing economic globalization, the scale of transportation through ports and waterways has increased sharply. As the capacity of maritime infrastructure in ports and inland waterways is limited, it is important to simulate vessel behavior to balance safety and capacity in restricted waterways. Currently many existing vessel...
journal article 2015
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Hartjes, S. (author)
Civil aviation plays an irreplaceable role in the current global civilization. Even though the 2008 economic crisis has limited growth in the western world, it can only be expected that due to continuing development in the Far East, South America and Africa this role will increase further over the years to come. Also in the field of helicopter...
doctoral thesis 2015
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Govindarajan, N. (author), De Visser, C.C. (author), Krishnakumar, K. (author)
This paper presents a sparse collocation method for solving the time-dependent Hamilton–Jacobi–Bellman (HJB) equation associated with the continuous-time optimal control problem on a fixed, finite timehorizon with integral cost functional. Through casting the problem in a recursive framework using the value iteration procedure, the value...
journal article 2014
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Govindarjan, N. (author), De Visser, C.C. (author), Van Kampen, E. (author), Krishnakumar, K. (author), Barlow, J. (author), Stepanyan, V. (author)
This paper presents an optimal control framework to determine a collection of open-loop command signals that mathematically guarantees operation of an aircraft within certain prescribed state constraints. The framework is specifically applied to estimate margins for the reference command inputs of aircraft autopilot systems, so that safe...
journal article 2014
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Bakker, M. (author), Rajewicz, T. (author), Kien, H. (author), Vreeburg, J.H.G. (author), Rietveld, L.C. (author)
Conventional automatic production flow control and pump pressure control of water supply systems are robust and simple: production flow is controlled based on the level in the clear water reservoir and pump pressure is controlled on a static set-point. Recently, more advanced computer-based control methods were developed in which production flow...
journal article 2014
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Wang, M. (author), Treiber, M. (author), Daamen, W. (author), Hoogendoorn, S.P. (author), Van Arem, B. (author)
Driver assistance systems support drivers in operating vehicles in a safe, comfortable and efficient way, and thus may induce changes in traffic flow characteristics. This paper puts forward a receding horizon control framework to model driver assistance and cooperative systems. The accelerations of automated vehicles are controlled to optimise...
journal article 2013
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Wang, M. (author), Daamen, W. (author), Hoogendoorn, S.P. (author), van Arem, B. (author)
Driver assistance systems support drivers in operating vehicles in a safe, comfortable and efficient way, and thus may induce changes in traffic flow characteristics. This paper put forward a receding horizon control framework to model driver assistance systems. The accelerations of automated vehicles are determined to optimise a cost function,...
conference paper 2012
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Song, H. (author)
Adaptive optics (AO), also called as Smart Optics, has received increasing attention in the past decades. The main idea behind AO is to actively sense and compensate the optical aberration in the system such that the image resolution is improved or the light beam is well focused. The applications of AO include ground-based telescopes, scanning...
doctoral thesis 2011
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Van Essen, G.M. (author), Van den Hof, P.M.J. (author), Jansen, J.D. (author)
In oil production waterflooding is a popular recovery technology, which involves the injection of water into an oil reservoir. Studies on model-based dynamic optimization of waterflooding strategies have demonstrated that there is a signifcant potential to increase life-cycle performance, measured in Net Present Value. However, in these studies...
conference paper 2010
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