Searched for: subject%3A%22Approximate%255C+dynamic%255C+programming%22
(1 - 16 of 16)
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He, K. (author), Shi, S. (author), van den Boom, A.J.J. (author), De Schutter, B.H.K. (author)
Approximate dynamic programming (ADP) faces challenges in dealing with constraints in control problems. Model predictive control (MPC) is, in comparison, well-known for its accommodation of constraints and stability guarantees, although its computation is sometimes prohibitive. This paper introduces an approach combining the two methodologies...
journal article 2024
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Fu, Bin (author), Sun, B. (author), Guo, Hang (author), Yang, Tao (author), Fu, Wenxing (author)
The current study presents an online iterative adaptive dynamic programming approach to resolve the zero-sum game (ZSG) for nonlinear continuous-time (CT) systems containing a partially unknown dynamic. The Hamilton-Jacobian-Issacs (HJI) equation is solved along the state trajectory according to the value function approximation and the policy...
conference paper 2023
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Vinks, Ties (author)
The global market for personal mobility has transformed over the last decade. Traditional taxi services have to compete with the emergence of ride-hailing services such as Uber and Lyft. Rapid developments in available algorithms and real-time inter-connectivity of travellers and vehicles offer mobility-on-demand (MOD) services new possibilities...
master thesis 2022
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Alves Beirigo, B. (author), Schulte, F. (author), Negenborn, R.R. (author)
Current mobility services cannot compete on equal terms with self-owned mobility products concerning service quality. Because of supply and demand imbalances, ridesharing users invariably experience delays, price surges, and rejections. Traditional approaches often fail to respond to demand fluctuations adequately because service levels are,...
journal article 2022
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Rodopoulos, Charalampos (author)
In decision making problems, the ability to compute the optimal solution can pose a serious challenge. Dynamic Programming (DP) aims to provide a framework to deal with a category of such problems, namely ones that involve sequential decision making. By dividing the original control problem into sub-problems and solving it backwards in time,...
master thesis 2021
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Alves Beirigo, B. (author)
Autonomous vehicles (AVs) have been heralded as the key to unlock a shared mobility future where transportation is more efficient, convenient, and cheaper. However, the AV utopia can only come to fruition if the majority of users trust that autonomous mobility-on-demand (AMoD) systems are on a par with owning a vehicle in terms of service...
doctoral thesis 2021
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Deng, Q. (author), Santos, Bruno F. (author)
This paper proposes a lookahead approximate dynamic programming methodology for aircraft maintenance check scheduling, considering the uncertainty of aircraft daily utilization and maintenance check elapsed time. It adopts a dynamic programming framework, using a hybrid lookahead scheduling policy. The hybrid lookahead scheduling policy makes...
journal article 2021
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Konatala, Ramesh (author)
Online Adaptive Flight Control is interesting in the context of growing complexity of aircraft systems and their adaptability requirements to ensure safety. An Incremental Approximate Dynamic Programming (iADP) controller combines reinforcement learning methods, optimal control and Online identified incremental model to achieve optimal adaptive...
master thesis 2020
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Wang, Pengling (author), Trivella, Alessio (author), Goverde, R.M.P. (author), Corman, Francesco (author)
In this paper we study the problem of computing train trajectories in an uncertain environment in which the values of some system parameters are difficult to determine. Specifically, we consider uncertainty in traction force and train resistance, and their impact on travel time and energy consumption. Our ultimate goal is to be able to...
journal article 2020
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Alves Beirigo, B. (author), Schulte, F. (author), Negenborn, R.R. (author)
Residents of cities’ most disadvantaged areas face significant barriers to key life activities, such as employment, education, and healthcare, due to the lack of mobility options. Shared autonomous vehicles (SAVs) create an opportunity to overcome this problem. By learning user demand patterns, SAV providers can improve regional service...
conference paper 2020
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Sutter, Tobias (author), Sutter, David (author), Mohajerin Esfahani, P. (author), Lygeros, John (author)
We consider the problem of estimating a probability distribution that maximizes the entropy while satisfying a finite number of moment constraints, possibly corrupted by noise. Based on duality of convex programming, we present a novel approximation scheme using a smoothed fast gradient method that is equipped with explicit bounds on the...
journal article 2019
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Zhou, Y. (author)
Reinforcement Learning (RL) methods are relatively new in the field of aerospace guidance, navigation, and control. This dissertation aims to exploit RL methods to improve the autonomy and online learning of aerospace systems with respect to the a priori unknown system and environment, dynamical uncertainties, and partial observability. In the...
doctoral thesis 2018
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Mohajerin Esfahani, P. (author), Sutter, Tobias (author), Kuhn, Daniel (author), Lygeros, John (author)
We consider linear programming (LP) problems in infinite dimensional spaces that are in general computationally intractable. Under suitable assumptions, we develop an approximation bridge from the infinite dimensional LP to tractable finite convex programs in which the performance of the approximation is quantified explicitly. To this end, we...
journal article 2018
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Requeno García, Laura (author)
This MSc thesis presents a stochastic modelling approach to the multi-period airline fleet planning problem. Approximate Dynamic Programming (ADP) is used to model the impact of demand uncertainty on fleet decisions. The proposed ADP algorithm applies local value function approximations resulting from Gaussian kernel regressions to estimate...
master thesis 2017
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Zhou, Y. (author), van Kampen, E. (author), Chu, Q. P. (author)
This paper presents an adaptive control technique to deal with spacecraft attitude tracking and disturbance rejection problems in the presence of model uncertainties. Approximate dynamic programming has been proposed to solve adaptive, optimal control problems without using accurate systems models. Within this category, linear approximate...
conference paper 2017
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Snoeij, V. (author)
Over the years gradually flight management systems have been added to airplanes which reduce pilot workload and increase safety. These systems however do not provide an adequate response when in an emergency situation the aircraft loses all thrust. A system that creates glide trajectories to airports that are reachable would enable pilots to...
master thesis 2016
Searched for: subject%3A%22Approximate%255C+dynamic%255C+programming%22
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