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Max, Gyula (author)A well-established method for finding the optimal control policy for a given dynamical system is to solve the problem iteratively going from its terminal state "backwards" in time, known as Dynamic Programming Algorithm. For a generic problem with discrete state/action space, the algorithm has computational complexity of <i>O(NM)</i> for <i>N</i...master thesis 2019
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Sekoor Lakshmana Sankar, Prajish (author)Wheeled-legged (hybrid) robots have the potential for highly agile and versatile locomotion in any real-world application requiring rapid, long-distance mobility skills on challenging terrain. The ability to walk and drive simultaneously is an attractive feature of these hybrid systems, but is unexplored in literature. This thesis work presents...master thesis 2019
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Sheth, Nilay (author)The e-sport of drone-racing involves human pilots to race against time. Recently, drone races have also gone fully-autonomous. As a result, these agile robotic platforms not only pose challenges of flying fast to the participating pilots but also create challenges for the flight control computers. As a result, the concept of autonomous drone...master thesis 2019
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Mulder, Justin (author)This thesis develops a method to forecast the cash flows that determine the value of an enterprise. From a control engineers perspective, three stages arise to develop such a method: the research, the system and the control part. The research part presents the results of a control theoretic analysis of PricewaterhouseCoopers’ (PwC) valuation...master thesis 2019
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Maene, Jochim (author)The past decade has seen a continuous increase of Earth observation missions, since they are regarded as an important tool to address global problems such as climate change or disaster mitigation. A commercial trend exists now towards higher resolution imagery, which drives the use of agile satellites. Nevertheless, a disadvantage of agile...master thesis 2019
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Coimbatore Anand, Sribalaji (author)Traditional centralized power plants have limited ability to adapt to the varying power demands caused due to the increasing deployment of renewable energy sources. For power grids, willing to increase the use of renewable energy and thereby decrease the energy bills, demand side energy management could act as an effective solution. Demand side...master thesis 2019
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Chowdhri, Nishant (author)The automotive sector has seen a rapid transition towards autonomous driving with an aim to achieve SAE Level 5 vehicle. The incessant drive for innovation has resulted in modern passenger cars equipped with plethora of control technologies such as ABS, VSC, AFS via EPS assist etc. all working respectively in various critical and non-critical...master thesis 2019
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van Weperen, Marijke (author)In recent years, rapid progress has been made towards automated highway driving. To increase comfort and trust in these automated cars, their motion planners, such as Model Predictive Controllers (MPCs), should exhibit a human-like driving style. However the effect of surrounding traffic on overtaking maneuvers has not yet been investigated....master thesis 2019
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Evans, Michael (author), Angeli, David (author), Strbac, Goran (author), Tindemans, Simon 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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Faassen, Gilles (author)In the automotive industry automation is popular and every year car OEMs advance their technology to be able to drive autonomously. Longitudinal control of the vehicles is an important part of the complete autonomous driving system. The difficulty of this control problem lies with changing longitudinal dynamics and the lack of full-state system...master thesis 2019
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Verdier, C.F. (author), Babuska, R. (author), Shyrokau, B. (author), Mazo, M. (author)Control systems designed via learning methods, aiming at quasi-optimal solutions, typically lack stability and performance guarantees. We propose a method to construct a near-optimal control law by means of model-based reinforcement learning and subsequently verifying the reachability and safety of the closed-loop control system through an...journal article 2019
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Evans, Michael P. (author), Tindemans, Simon H. (author), Angeli, David (author)This paper considers the optimal dispatch of energy-constrained heterogeneous storage units to maximize security of supply. A policy, requiring no knowledge of the future, is presented and shown to minimize unserved energy during supply-shortfall events, regardless of the supply and demand profiles. It is accompanied by a graphical means to...journal article 2019
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Lago, Jesus (author), De Ridder, Fjo (author), Mazairac, Wiet (author), De Schutter, B.H.K. (author)To mitigate the effects of the intermittent generation of renewable energy sources, reliable and efficient energy storage is critical. Since nearly 80% of households energy consumption is destined to water and space heating, thermal energy storage is particularly important. In this context, we propose and validate a new model for one of the...journal article 2019
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Baldi, S. (author), Michailidis, Iakovos (author), Ntampasi, Vasiliki (author), Kosmatopoulos, Elias (author), Papamichail, Ioannis (author), Papageorgiou, Markos (author)Traffic congestion in urban networks may lead to strong degradation in the utilization of the network infrastructure, which can be mitigated via suitable control strategies. This paper studies and analyzes the performance of an adaptive traffic-responsive strategy that controls the traffic light parameters in an urban network to reduce...journal article 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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Bijl, H.J. (author), Schön, Thomas B. (author)The linear–quadratic-Gaussian (LQG) control paradigm is well-known in literature. The strategy of minimizing the cost function is available, both for the case where the state is known and where it is estimated through an observer. The situation is different when the cost function has an exponential discount factor, also known as a prescribed...journal article 2019
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van der Spaa, L.F. (author), Wolfslag, W.J. (author), Wisse, M. (author)In electrically actuated robots most energy losses are due to the heating of the actuators. This energy loss can be greatly reduced with parallel elastic actuators, by optimizing the elastic element such that it delivers most of the required torques. Previously used optimization methods relied on parameterizing the spring characteristic,...journal article 2019
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Hoogerwerf, Eert (author)Human-robot collaboration can be improved if the motions of the robot are more legible and predictable. This can be achieved by making the motions more human-like. It is assumed that humans move optimal with respect to a certain objective or cost function. To find this function an inverse optimal control approach is developed. It uses a bilevel...master thesis 2018
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Koryakovskiy, I. (author)Reinforcement learning is an active research area in the fields of artificial intelligence and machine learning, with applications in control. The most important feature of reinforcement learning is its ability to learn without prior knowledge about the system. However, in the real world, reinforcement learning actions may lead to serious damage...doctoral thesis 2018
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Petersen, Co (author)The most common operational measure in aviation to reduce the effect of environmental noise pollution is noise abatement procedures. Noise abatement procedures are recommended flying techniques based on noise optimal trajectories, which aim at reducing the noise impact on local communities as much as possible. Atmospheric...master thesis 2018