| 2601. |
- Gao, Yulong, 1990-
(författare)
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Safe Autonomy under Uncertainty: Computation, Control, and Application
- 2020
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Safety is a primary requirement for many autonomous systems, such as automated vehicles and mobile robots. An open problem is how to assure safety, in the sense of avoiding unsafe subsets of the state space, for uncertain systems under complex tasks. In this thesis, we solve this problem for certain system classes and uncertainty descriptions by developing computational tools, designing verification and control synthesis algorithms, and evaluating them on two applications.As our first contribution, we consider how to compute probabilistic controlled invariant sets, which are sets the controller is able to keep the system state within with a certain probability. By using stochastic backward reachability, we design algorithms to compute these sets. We prove that the algorithms are computationally tractable and converge in a finite number of iterations. We further consider how to compute invariant covers, which are covers of sets that can be enforced to be invariant by a finite number of control inputs despite disturbances.A necessary and sufficient condition on the existence of an invariant cover is derived. Based on this result, an efficient computational algorithm is designed.The second contribution is to develop algorithms for model checking and control synthesis. We consider discrete-time uncertain systems under linear temporal logic (LTL) specifications. We propose the new notion of temporal logic trees (TLT) and show how to construct TLT from LTL formulae via reachability analysis for both autonomous and controlled transition systems. We prove approximation relations between TLT and LTL formulae. Two sufficient conditions are given to verify whether a transition system satisfies an LTL formula. An online control synthesis algorithm, under which a set of feasible control inputs can be generated at each time step, is designed, and it is proven to be recursively feasible.As our third contribution, we study two important vehicular applications on shared-autonomy systems, which are systems with a mix of human and automated decisions. For the first application, we consider a car parking problem, where a remote human operator is guided to drive a vehicle to an empty parking spot. An automated controller is designed to guarantee safety and mission completion despite unpredictable human actions. For the second application, we consider a car overtaking problem, where an automated vehicle overtakes a human-driven vehicle with uncertain motion. We design a risk-aware optimal overtaking algorithm with guaranteed levels of safety.
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| 2602. |
- Gao, Yulong
(författare)
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Stochastic Invariance and Aperiodic Control for Uncertain Constrained Systems
- 2018
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Uncertainties and constraints are present in most control systems. For example, robot motion planning and building climate regulation can be modeled as uncertain constrained systems. In this thesis, we develop mathematical and computational tools to analyze and synthesize controllers for such systems.As our first contribution, we characterize when a set is a probabilistic controlled invariant set and we develop tools to compute such sets. A probabilistic controlled invariantset is a set within which the controller is able to keep the system state with a certainprobability. It is a natural complement to the existing notion of robust controlled invariantsets. We provide iterative algorithms to compute a probabilistic controlled invariantset within a given set based on stochastic backward reachability. We prove that thesealgorithms are computationally tractable and converge in a finite number of iterations. The computational tools are demonstrated on examples of motion planning, climate regulation, and model predictive control.As our second contribution, we address the control design problem for uncertain constrained systems with aperiodic sensing and actuation. Firstly, we propose a stochastic self-triggered model predictive control algorithm for linear systems subject to exogenous disturbances and probabilistic constraints. We prove that probabilistic constraint satisfaction, recursive feasibility, and closed-loop stability can be guaranteed. The control algorithm is computationally tractable as we are able to reformulate the problem into a quadratic program. Secondly, we develop a robust self-triggered control algorithm for time-varying and uncertain systems with constraints based on reachability analysis. In the particular case when there is no uncertainty, the design leads to a control system requiring minimum number of samples over finite time horizon. Furthermore, when the plant is linear and the constraints are polyhedral, we prove that the previous algorithms can be reformulated as mixed integer linear programs. The method is applied to a motion planning problem with temporal constraints.
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| 2603. |
- Gao, Yulong, et al.
(författare)
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Stochastic Modeling and Optimal Control for Automated Overtaking
- 2019
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Ingår i: Proceedings of the IEEE Conference on Decision and Control. - : Institute of Electrical and Electronics Engineers Inc.. - 9781728113982 ; , s. 1273-1278
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Konferensbidrag (refereegranskat)abstract
- This paper proposes a solution to the overtaking problem where an automated vehicle tries to overtake a human-driven vehicle, which may not be moving at a constant velocity. Using reachability theory, we first provide a robust time-optimal control algorithm to guarantee that there is no collision throughout the overtaking process. Following the robust formulation, we provide a stochastic reachability formulation that allows a trade-off between the conservative overtaking time and the allowance of a small collision probability. To capture the stochasticity of a human driver's behavior, we propose a new martingale-based model where we classify the human driver as aggressive or nonaggressive. We show that if the human driver is nonaggressive, our stochastic time-optimal control algorithm can provide a shorter overtaking time than our robust algorithm, whereas if the human driver is aggressive, the stochastic algorithm will act on a collision probability of zero, which will match the robust algorithm. Finally, we detail a simulated example that illustrates the effectiveness of the proposed algorithms.
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| 2604. |
- Gao, Yulong, et al.
(författare)
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Stochastic Optimal Control of Dynamic Queue Systems : A Probabilistic Perspective
- 2018
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Ingår i: 2018 15TH INTERNATIONAL CONFERENCE ON CONTROL, AUTOMATION, ROBOTICS AND VISION (ICARCV). - : IEEE. - 9781538695821 ; , s. 837-842
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Konferensbidrag (refereegranskat)abstract
- Queue overflow of a dynamic queue system gives rise to the information loss (or packet loss) in the communication buffer or the decrease of throughput in the transportation network. This paper investigates a stochastic optimal control problem for dynamic queue systems when imposing probability constraints on queue overflows. We reformulate this problem as a Markov decision process (MDP) with safety constraints. We prove that both finite-horizon and infinite-horizon stochastic optimal control for MDP with such constraints can be transformed as a linear program (LP), respectively. Feasibility conditions are provided for the finite-horizon constrained control problem. Two implementation algorithms are designed under the assumption that only the state (not the state distribution) can be observed at each time instant. Simulation results compare optimal cost and state distribution among different scenarios, and show the probability constraint satisfaction by the proposed algorithms.
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| 2605. |
- Gao, Yulong, et al.
(författare)
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Temporal Logic Trees for Model Checking and Control Synthesis of Uncertain Discrete-time Systems
- 2021
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Ingår i: IEEE Transactions on Automatic Control. - : Institute of Electrical and Electronics Engineers (IEEE). - 0018-9286 .- 1558-2523. ; , s. 1-1
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Tidskriftsartikel (refereegranskat)abstract
- We propose algorithms for performing model checking and control synthesis for discrete-time uncertain systems under linear temporal logic (LTL) specifications. We construct temporal logic trees (TLT) from LTL formulae via reachability analysis. In contrast to automaton-based methods, the construction of the TLT is abstraction-free for infinite systems, that is, we do not construct discrete abstractions of the infinite systems. Moreover, for a given transition system and an LTL formula, we prove that there exist both a universal TLT and an existential TLT via minimal and maximal reachability analysis, respectively. We show that the universal TLT is an underapproximation for the LTL formula and the existential TLT is an overapproximation. We provide sufficient conditions and necessary conditions to verify whether a transition system satisfies an LTL formula by using the TLT approximations. As a major contribution of this work, for a controlled transition system and an LTL formula, we prove that a controlled TLT can be constructed from the LTL formula via control-dependent reachability analysis. Based on the controlled TLT, we design an online control synthesis algorithm, under which a set of feasible control inputs can be generated at each time step. We also prove that this algorithm is recursively feasible. We illustrate the proposed methods for both finite and infinite systems and highlight the generality and online scalability with two simulated examples.
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| 2606. |
- Garde, Adam A., et al.
(författare)
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The Finnefjeld domain, Maniitsoq structure, West Greenland: Differential rheological features and mechanical homogenisation in response to impacting?
- 2014
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Ingår i: Precambrian Research. - : Elsevier BV. - 0301-9268. ; 255, s. 791-808
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Tidskriftsartikel (refereegranskat)abstract
- The 35 by 50 km large, Mesoarchaean Finnefjeld domain near Maniitsoq in the North Atlantic craton of southern West Greenland constitutes the central part of the previously proposed, deeply eroded Maniitsoq impact structure with an age of 3.0 Ga. The Finnefjeld domain is an exceedingly homogeneous, quartzo-feldspathic rock mass which superficially appears to be a late-orogenic, deep-crustal, intrusive granitoid pluton, and which was described as such for decades. However, new observations confirm and qualify the first observations from 1962 of these rocks as 'cataclastic'. The Finnefjeld domain is characterised by a highly unusual, mixed rheological behaviour. Plagioclase displays brittle behaviour with cataclasis, quartz was ductilely deformed, and K-feldspar was melted. The deformation and homogenisation of the Finnefjeld domain was caused by an intense event of heating and deformation, which was coseismic in nature and comprised numerous increments of pure shear strain. This type of intense, brittle, regional deformation and concomitant direct mineral melting in the deep crust is unknown from endogenic orogenic events and is ascribed to deep-crustal effects of impacting. (C) 2014 Elsevier B.V. All rights reserved.
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| 2607. |
- Garin, Federica, et al.
(författare)
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Distributed estimation of diameter, radius and eccentricities in anonymous networks
- 2012
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Ingår i: Estimation and Control of Networked Systems, Vol 3. Part 1. - : IFAC. ; , s. 13-18
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Konferensbidrag (refereegranskat)abstract
- We consider how a set of collaborating agents can distributedly infer some of the properties of the communication network that they form. We specifically focus on estimating quantities that can characterize the performance of other distributed algorithms, namely the eccentricities of the nodes, and the radius and diameter of the network. We propose a strategy that can be implemented in any network, even under anonymity constraints, and has the desirable properties of being fully distributed, parallel and scalable. We analytically characterize the statistics of the estimation error, and highlight how the performance of the algorithm depends on a parameter tuning the communication complexity.
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| 2608. |
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| 2609. |
- Garza, Raquel, et al.
(författare)
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LINE-1 retrotransposons drive human neuronal transcriptome complexity and functional diversification
- 2023
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Ingår i: Science Advances. - 2375-2548. ; 9:44
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Tidskriftsartikel (refereegranskat)abstract
- The genetic mechanisms underlying the expansion in size and complexity of the human brain remain poorly understood. Long interspersed nuclear element-1 (L1) retrotransposons are a source of divergent genetic information in hominoid genomes, but their importance in physiological functions and their contribution to human brain evolution are largely unknown. Using multiomics profiling, we here demonstrate that L1 promoters are dynamically active in the developing and the adult human brain. L1s generate hundreds of developmentally regulated and cell type-specific transcripts, many that are co-opted as chimeric transcripts or regulatory RNAs. One L1-derived long noncoding RNA, LINC01876, is a human-specific transcript expressed exclusively during brain development. CRISPR interference silencing of LINC01876 results in reduced size of cerebral organoids and premature differentiation of neural progenitors, implicating L1s in human-specific developmental processes. In summary, our results demonstrate that L1-derived transcripts provide a previously undescribed layer of primate- and human-specific transcriptome complexity that contributes to the functional diversification of the human brain.
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| 2610. |
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