Searched for: subject%3A%22optimal%255C%2Bcontrol%22
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Swannet, Kilian (author)
Interest grows rapidly in electric and hybrid electric aircraft. To determine the optimal performance and energy management required with such novel powertrain configurations, a knowledge-based aircraft and powertrain performance model is developed. The model is then used to set up an optimal control problem, which is transcribed to a non-linear...
master thesis 2022
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Pesselse, Mike (author)
Inland waterways form a natural network infrastructure with the capacity for waterborne transport of people and goods for moving freight from seaports to the hinterland. Recently, Inland Waterway Transport (IWT) has been promoted more extensively by the European Union and various governments as it plays a crucial role in reducing road congestion...
master thesis 2022
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Li, S. (author), de Wagter, C. (author), de Croon, Guido C.H.E. (author)
Wireless ranging measurements have been proposed for enabling multiple Micro Air Vehicles (MAVs) to localize with respect to each other. However, the high-dimensional relative states are weakly observable due to the scalar distance measurement. Hence, the MAVs have degraded relative localization and control performance under unobservable...
journal article 2022
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Verdier, C.F. (author), Kochdumper, Niklas (author), Althoff, Matthias (author), Mazo, M. (author)
We propose a counterexample-guided inductive synthesis framework for the formal synthesis of closed-form sampled-data controllers for nonlinear systems to meet STL specifications over finite-time trajectories. Rather than stating the STL specification for a single initial condition, we consider an (infinite and bounded) set of initial...
journal article 2022
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Dimanidis, Ioannis (author)
We propose a novel method combining elements of supervised- and Q-learning for the control of dynamical systems subject to unknown disturbances. By using the Inverse Optimization framework and in-hindsight information we can derive a causal parametric optimization policy that approximates a non-causal MPC expert. Furthermore, we propose a new...
master thesis 2021
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van Adrichem, Romeo (author)
Due to the short shelf-life of flowers (circa 7 days) good inventory management is required to minimize disposals. The trade-off between supplying enough to meet demand yet not too much to prevent expiration is a delicate matter. However, in the current situation uncertainty about inventory levels due to inadequate information and conventional...
master thesis 2021
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Suresh Kumar, Sandeep (author)
It is anticipated that for the automated driving industry to grow, public acceptance is required. The trust and acceptance of automated vehicles are primarily dependent on the travelling experience of people. In automated vehicles, passengers are expected to be engaged in non-driving tasks that are likely to decrease their predictability of the...
master thesis 2021
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Chotalal, Rohan (author)
For most robotics applications, optimal control remains a promising solution for solving complex control tasks. One example is the time-optimal flight of Micro Air Vehicles (MAVs), where strict computational requirements fail to resolve such algorithms onboard. Recent work on the use of deep neural networks for guidance and control (G&CNets)...
master thesis 2021
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Klein Schiphorst, Jonathan (author)
Stability, safety and optimality are often sought-after properties in the field of controller synthesis. In the last century, linear control theory has matured to a level where scalable algorithms are widely available that are able to synthesize controllers with stability and optimality guarantee. However, the synthesis of safe controllers...
master thesis 2021
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Westenberger, Jelle (author)
Time-optimal model-predictive control is essential in achieving fast and adaptive quadcopter flight. Due to the limited computational performance of onboard hardware, aggressive flight approaches have relied on off-line trajectory optimization processes or non time-optimal methods. In this work we propose a computational efficient model...
master thesis 2021
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Chowdhri, Nishant (author), Ferranti, L. (author), Santafé Iribarren, Felipe (author), Shyrokau, B. (author)
This work presents a Nonlinear Model Predictive Control (NMPC) scheme to perform evasive maneuvers and avoid rear-end collisions. Rear-end collisions are among the most common road fatalities. To reduce the risk of collision, it is necessary for the controller to react as quickly as possible and exploit the full vehicle maneuverability (i.e.,...
journal article 2021
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Kubalik, Jiri (author), Derner, Erik (author), Zegklitz, Jan (author), Babuska, R. (author)
Reinforcement learning algorithms can solve dynamic decision-making and optimal control problems. With continuous-valued state and input variables, reinforcement learning algorithms must rely on function approximators to represent the value function and policy mappings. Commonly used numerical approximators, such as neural networks or basis...
journal article 2021
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de Groot, O.M. (author), Ferreira de Brito, B.F. (author), Ferranti, L. (author), Gavrila, D. (author), Alonso Mora, J. (author)
We present an optimization-based method to plan the motion of an autonomous robot under the uncertainties associated with dynamic obstacles, such as humans. Our method bounds the marginal risk of collisions at each point in time by incorporating chance constraints into the planning problem. This problem is not suitable for online optimization...
journal article 2021
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van der Kruk, E. (author), Silverman, Anne K. (author), Koizia, Louis (author), Reilly, Peter (author), Fertleman, Michael (author), Bull, Anthony M.J. (author)
The prevention, mitigation and treatment of movement impairments, ideally, requires early diagnosis or identification. As the human movement system has physiological and functional redundancy, movement limitations do not promptly arise at the onset of physical decline. A such, prediction of movement limitations is complex: it is unclear how...
journal article 2021
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Sun, B. (author), van Kampen, E. (author)
The scarcity of information regarding dynamics and full-state feedback increases the demand for a model-free control technique that can cope with partial observability. To deal with the absence of prior knowledge of system dynamics and perfect measurements, this paper develops a novel intelligent control scheme by combining global dual...
journal article 2021
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Rakhshani, E. (author), Naveh, Iman Mohammad Hosseini (author), Mehrjerdi, Hasan (author)
This paper presents a new application of advanced SMPI controller for a newly introduced interconnected dynamic system with VSP based HVDC links for frequency control problem. This work presents an outgrowth of analysis about the Swarm – Based Optimization Algorithms (SBOAs) in the tuning process of Multivariable Proportional – Integral (MPI)...
journal article 2021
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Armenta, Carlos (author), Delprat, Sebastien (author), Negenborn, R.R. (author), Haseltalab, A. (author), Lauber, Jimmy (author), Dambrine, Michel (author)
Pontryagin’s Minimum Principle is a way of solving hybrid powertrain optimal energy management. This paper presents an improvement of a classical implementation. The core of this improvement consists in relaxing the tolerance on some intermediate steps of the algorithm in order to reduce the number of iterations and thereby reducing the...
journal article 2021
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Kraaij, R.C. (author), Schlottke, Mikola C. (author)
We study the well-posedness of Hamilton–Jacobi–Bellman equations on subsets of R<sup>d</sup> in a context without boundary conditions. The Hamiltonian is given as the supremum over two parts: an internal Hamiltonian depending on an external control variable and a cost functional penalizing the control. The key feature in this paper is that...
journal article 2021
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Pfeiffer, S.U. (author), de Wagter, C. (author), de Croon, G.C.H.E. (author)
We present a computationally efficient moving horizon estimator that allows for real-time localization using Ultra-Wideband measurements on small quadrotors. The estimator uses only a single iteration of a simple gradient descent method to optimize the state estimate based on past measurements, while using random sample consensus to reject...
journal article 2021
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Gravell, Benjamin (author), Mohajerin Esfahani, P. (author), Summers, Tyler H. (author)
The linear quadratic regulator (LQR) problem has reemerged as an important theoretical benchmark for reinforcement learning-based control of complex dynamical systems with continuous state and action spaces. In contrast with nearly all recent work in this area, we consider multiplicative noise models, which are increasingly relevant because...
journal article 2021
Searched for: subject%3A%22optimal%255C%2Bcontrol%22
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