| 1. |
- Björk, Joakim, 1989-
(författare)
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Fundamental Control Performance Limitations for Interarea Oscillation Damping and Frequency Stability
- 2021
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- With the transition towards renewable energy and the deregulation of the electricity markets, the power system is changing. Growing electricity demand and more intermittent power production increase the need for transfer capacity. Lower inertia levels due to a higher share of renewables increase the need for fast frequency reserves (FFR). In this thesis, we study fundamental control limitations for improving the damping of interarea oscillations and frequency stability.The first part of the thesis considers the damping of oscillatory interarea modes. These system-wide modes involve power oscillating between groups of generators and are sometimes hard to control due to their scale and complexity. We consider limitations of decentralized control schemes based on local measurements, as well as centralized control schemes with limitations associated to actuator dynamics and network topology. It is shown that the stability of asynchronous grids can be improved by modulating the active power of a single interconnecting high-voltage direct current (HVDC) link. One challenge with modulating HVDC active power is that the interaction between interarea modes of the two grids may have a negative impact on system stability. By studying the controllability Gramian, we show that it is possible to improve the damping in both grids as long as the frequencies of their interarea modes are not too close. It is demonstrated how the controllability, and therefore the achievable damping, deteriorates as the frequency difference becomes small. With a modal frequency difference of 5%, the damping can be improved by around 2 percentage points whereas a modal frequency difference of 20% allows for around 8 percentage points damping improvement. The results are validated by simulating two HVDC-interconnected 32-bus power system models. We also consider the coordinated control of two and more HVDC links. For some network configurations, it is shown that the interaction between troublesome interarea modes can be avoided. The second part considers the coordination of frequency containment reserves (FCR) in low-inertia power systems. A case study is performed in a 5-machine model of the Nordic synchronous grid. We consider a low-inertia test case where FCR are provided by hydro power. The non-minimum phase characteristic of the waterways limits the achievable bandwidth of the FCR control. It is shown that a consequence of this is that hydro-FCR fails at keeping the frequency nadir above the 49.0 Hz safety limit following the loss of a HVDC link that imports 1400 MW. To improve the dynamic frequency stability, FFR from wind power is considered. For this, a new wind turbine model is developed. The turbine is controlled at variable-speed, enabling FFR by temporarily borrowing energy from the rotating turbine. The nonlinear wind turbine dynamics are linearized to facilitate a control design that coordinate FFR from the wind with slow FCR from hydropower. Complementary wind resources with a total rating of 2000 MW, operating at 70–90% rated wind speeds, is shown to be more than enough to fulfill the frequency stability requirements. The nadir is kept above 49.0 Hz without the need to install battery storage or to waste wind energy by curtailing the wind turbines.
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| 2. |
- Johansson, Alexander
(författare)
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Coordination of cross-carrier truck platooning
- 2022
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The need for sustainable transportation solutions is urgent as the demand for mobility of goods and people is expected to multiply in the upcoming decades. One promising solution is truck platooning, which shows great potential in reducing the energy consumption and operational costs of trucks. To utilize the benefits of truck platooning to the fullest, trucks with different schedules and routes in a road network need coordination to form platoons. This thesis addresses platoon coordination when trucks can wait at hubs to form platoons. We assume there is a reward for driving in a platoon and a cost for waiting at a hub, and the objective is to maximize the overall profit. We focus on coordinating trucks from different carriers, which is important considering that many platoon opportunities are lost if only trucks from the same carrier form platoons.In the first contributions of the thesis, we propose coordination solutions where carriers aim to maximize their own profits through cross-carrier platoon cooperation. We propose an architecture of a platoon-hailing service that stores reported platooning plans of carriers and, based on these, informs carriers about the platoons their trucks can join when they make platooning decisions. A realistic simulation study shows that the cross-carrier platooning system can achieve energy savings of 3.0% and 5.4% when 20% and 100% of the trucks are coordinated, respectively. A non-cooperative game is then formulated to model the strategic interaction among trucks with individual objectives when they coordinate for platooning and make decisions at the beginning of their journeys. The existence of at least one Nash equilibrium is shown. In the case of stochastic travel times, feedback-based solutions are developed wherein trucks repeatedly update their equilibrium decisions. A simulation study with stochastic travel times shows that the feedback-based solutions achieve platooning rates only $5\%$ lower than a solution where the travel times are known. We also explore Pareto-improving coordination guaranteeing each carrier is better off coopering with others, and models for distributing the profit within platoons.In the last contributions of the thesis, we study the problem of optimally releasing trucks at hubs when arriving according to a stochastic process, and a priori information about truck arrivals is inaccessible; this may be sensitive information to share with others. First, we study the release problem at hubs in a hub-corridor where the objective is to maximize the profit over time. The optimality of threshold-based release policies is shown under the assumption that arrivals are independent or that arrivals are dependent due to the releasing behavior at the preceding hub in the corridor. Then, we study the release problem at a single hub where the aim is to maximize the profit of trucks currently at the hub. This is realistic if trucks are only willing to wait at the hub if they can increase their own profits. Stopping time theory is used to show the optimality of a threshold-based release policy when arrivals are independent and identically distributed. These contributions show that simple coordination approaches can achieve high profits from platooning, even under limited information.
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| 3. |
- Adaldo, Antonio
(författare)
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Event-triggered and cloud-support control of multi-robot systems
- 2018
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- In control of multi-robot systems, the aim is to obtain a coordinated behavior through local interactions among the robots. A multi-agent system is an abstract model of a multi-robot system. In this thesis, we investigate multi-agent systems where inter-agent communication is modeled by discrete events triggered by conditions on the internal state of the agents. We consider two models of communication. In the first model, two agents exchange information directly with each other. In the second model, all information is exchanged asynchronously over a shared repository. Four contributions on control algorithms for multi-agent systems are offered in the thesis. The first contribution is an event-triggered pinning control algorithm for a network of agents with nonlinear dynamics and time-varying topology. Pinning control is a strategy to steer the behavior of the system in a desired manner by controlling only a small fraction of the agents. We express the controllability of the network in terms of an average value of the network connectivity over time, and we show that all the agents can be driven to a desired reference trajectory. The second contribution is a control algorithm for multi-agent systems where inter-agent communication is substituted with a shared remote repository hosted on a cloud. The communication between each agent and the cloud is modeled as a sequence of events scheduled recursively by the agent. We quantify the connectivity of the network and we show that it is possible to synchronize the multi-agent system to the same state trajectory, while guaranteeing that two consecutive cloud accesses by the same agent are separated by a lower-bounded time interval. The third contribution is a family of distributed controllers for coverage and surveillance tasks with a network of mobile agents with anisotropic sensing patterns. We develop an abstract model of the environment under inspection and define a measure of the coverage attained by the sensor network. We show that the network attains nondecreasing coverage, and we characterize the equilibrium configurations of the network. The fourth contribution is a distributed, cloud-supported control algorithm for inspection of 3D structures with a network of mobile sensing agents, similar to those considered in the third contribution. We develop an abstract model of the structure to inspect and quantify the degree of completion of the inspection. We demonstrate that, under the proposed algorithm, the network is guaranteed to complete the inspection in finite time. All results presented in the thesis are corroborated by numerical simulations and sometimes by experiments with aerial robotic platforms. The experiments show that the theory and methods developed in the thesis are of practical relevance.
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| 4. |
- Alam, Assad, 1982-
(författare)
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Fuel-Efficient Heavy-Duty Vehicle Platooning
- 2014
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The freight transport industry faces big challenges as the demand for transport and fuel prices are steadily increasing, whereas the environmental impact needs to be significantly reduced. Heavy-duty vehicle (HDV) platooning is a promising technology for a sustainable transportation system. By semi-autonomously governing each platooning vehicle at small inter-vehicle spacing, we can effectively reduce fuel consumption, emissions, and congestion, and relieve driver tension. Yet, it is not evident how to synthesise such a platoon control system and how constraints imposed by the road topography affect the safety or fuel-saving potential in practice.This thesis presents contributions to a framework for the design, implementation, and evaluation of HDV platooning. The focus lies mainly on establishing fuel-efficient platooning control and evaluating the fuel-saving potential in practice. A vehicle platoon model is developed together with a system architecture that divides the control problem into manageable subsystems. Presented results show that a significant fuel reduction potential exists for HDV platooning and it is favorable to operate the vehicles at a small inter-vehicle spacing. We address the problem of finding the minimum distance between HDVs in a platoon without compromising safety, by setting up the problem in a game theoretical framework. Thereby, we determine criteria for which collisions can be avoided in a worst-case scenario and establish the minimum safe distance to a vehicle ahead. A systematic design methodology for decentralized inter-vehicle distance control based on linear quadratic regulators is presented. It takes dynamic coupling and engine response delays into consideration, and the structure of the controller feedback matrix can be tailored to the locally available state information. The results show that a decentralized controller gives good tracking performance and attenuates disturbances downstream in the platoon for dynamic scenarios that commonly occur on highways. We also consider the problem of finding a fuel-efficient controller for HDV platooning based on road grade preview information under road and vehicle parameter uncertainties. We present two model predictive control policies and derive their fuel-saving potential. The thesis finally evaluates the fuel savings in practice. Experimental results show that a fuel reduction of 3.9–6.5 % can be obtained on average for a heterogenous platoon of HDVs on a Swedish highway. It is demonstrated how the savings depend on the vehicle position in the platoon, the behavior of the preceding vehicles, and the road topography. With the results obtained in this thesis, it is argued that a significant fuel reduction potential exists for HDV platooning.
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| 5. |
- Alisic, Rijad
(författare)
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Defense of Cyber-Physical Systems Against Learning-based Attackers
- 2023
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Cyberattacks against critical infrastructures pose a serious threat to society, as they can have devastating consequences on the economy, security, or public health. These infrastructures rely on a large network of cyber components, such as sensors, controllers, computers, and communication devices, to monitor and control their physical processes. An adversary can exploit the vulnerabilities in these cyber components to gain access to the system and manipulate its behavior or functionality.This thesis proposes methods that can be employed as a first line of defense against such attacks for Cyber-Physical Systems. In the first part of the thesis, we consider how uninformed attackers can learn to attack a Cyber-Physical System by eavesdropping through the cyber component. By learning to manipulate the plant, the attacker could figure out how to destroy the physical system before it is too late or completely take it over without raising any alarms. Stopping the attacker at the learning stage would force the attacker to act obliviously, increasing the chances of detecting them.We analyze how homomorphic encryption, a technique that allows computation on encrypted data, hinders an attacker's learning process and reduces its capabilities to attack the system. Specifically, we show that an attacker must solve challenging lattice problems to find attacks that are difficult to detect. Additionally, we show how the detection probability is affected by the attacker's solution to the problems and what parameters of the encryption scheme can be tweaked to increase the detection probability. We also develop a novel method that enables anomaly detection over homomorphically encrypted data without revealing the actual signals to the detector, thereby discouraging attackers from launching attacks on the detector. The detection can be performed using a hypothesis test. However, special care must be taken to ensure that fresh samples are used to detect changes from nominal behavior. We also explore how the adversary can try to evade detection using the same test and how the system can be designed to make detection easier for the defender and more challenging for the attacker.In the second part of the thesis, we study how information leakage about changes in the system depends on the system's dynamics. We use a mathematical tool called the Hammersley-Chapman-Robbins lower bound to measure how much information is leaked and how to minimize it. Specifically, we study how structured input sequences, which we call events, can be obtained through the output of a dynamical system and how this information can be hidden by adding noise or changing the inputs. The system’s speed and sensor locations affect how much information is leaked. We also consider balancing the system’s performance and privacy when using optimal control. Finally, we show how to estimate when the adversary’s knowledge of the event becomes accurate enough to launch an attack and how to change the system before that happens. These results are then used to aid the operator in detecting privacy vulnerabilities when designing a Cyber-Physical System, which increases the overall security when removed.
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| 6. |
- Araújo, José, 1985-
(författare)
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Design, Implementation and Validation of Resource-Aware and Resilient Wireless Networked Control Systems
- 2014
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Networked control over wireless networks is of growing importance in many application domains such as industrial control, building automation and transportation systems. Wide deployment however, requires systematic design tools to enable efficient resource usage while guaranteeing close-loop control performance. The control system may be greatly affected by the inherent imperfections and limitations of the wireless medium and malfunction of system components. In this thesis, we make five important contributions that address these issues. In the first contribution, we consider event- and self-triggered control and investigate how to efficiently tune and execute these paradigms for appropriate control performance. Communication strategies for aperiodic control are devised, where we jointly address the selection of medium-access control and scheduling policies. Experimental results show that the best trade-off is obtained by a hybrid scheme, combining event- and self-triggered control together with contention-based and contention-free medium access control.The second contribution proposes an event-based method to select between fast and slow periodic sampling rates. The approach is based on linear quadratic control and the event condition is a quadratic function of the system state. Numerical and experimental results show that this hybrid controller is able to reduce the average sampling rate in comparison to a traditional periodic controller, while achieving the same closed-loop control performance.In the third contribution, we develop compensation methods for out-of-order communications and time-varying delays using a game-theoretic minimax control framework. We devise a linear temporal coding strategy where the sensor combines the current and previous measurements into a single packet to be transmitted. An experimental evaluation is performed in a multi-hop networked control scenario with a routing layer vulnerability exploited by a malicious application. The experimental and numerical results show the advantages of the proposed compensation schemes.The fourth contribution proposes a distributed reconfiguration method for sensor and actuator networks. We consider systems where sensors and actuators cooperate to recover from faults. Reconfiguration is performed to achieve model-matching, while minimizing the steady-state estimation error covariance and a linear quadratic control cost. The reconfiguration scheme is implemented in a room heating testbed, and experimental results demonstrate the method's ability to automatically reconfigure the faulty system in a distributed and fast manner.The final contribution is a co-simulator, which combines the control system simulator Simulink with the wireless network simulator COOJA. The co-simulator integrates physical plant dynamics with realistic wireless network models and the actual embedded software running on the networked devices. Hence, it allows for the validation of the complete wireless networked control system, including the study of the interactions between software and hardware components.
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| 7. |
- Barclay, Victoria K.H.
(författare)
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Development of LC-MS/MS Methods for the Analysis of Chiral and Achiral Pharmaceuticals and Metabolites in Aqueous Environmental Matrices
- 2012
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- This thesis describes the development of liquid chromatography tandem mass spectrometry (LC-MS/MS) methods for the trace analysis of active pharmaceutical ingredients (APIs) and their metabolites in aqueous environmental matrices. The research was focused on the development of chiral LC-MS/MS methods for the analysis of fluoxetine and metoprolol, as well as their chiral metabolites in environmental water samples. A method was also developed for the achiral compounds, diazepam and nordiazepam. The LC-MS/MS methods were validated by the use of the isotope-labeled compounds. As these isotope-labeled compounds were not found in the wastewater samples, the validation could be assessed at trace level concentrations in the actual matrices in which the analytes were detected. The analytes were extracted from the water samples using solid phase extraction methods. Different types of solid phase extraction sorbents were evaluated. Fluoxetine and norfluoxetine were extracted through the use of a mixed mode polymeric based extraction sorbent. A hydrophilic and lipophilic balanced sorbent was employed for the simultaneous extraction of metoprolol and its metabolites, the base α-hydroxymetoprolol and the acidic metabolite deaminated metoprolol. Moreover, silica based C18 extraction discs were applied for the sample preparation of diazepam and nordiazepam. The chromatographic separations were conducted in reversed phase LC with MS compatible mobile phases. The enantiomers of fluoxetine and norfluoxetine were simultaneously separated using the chiral stationary phase (CSP), α1-acid glycoprotein (AGP). The Chiral AGP column was also applied for the separation of the enantiomers of deaminated metoprolol. For the simultaneous separation of the metoprolol enantiomers and the four stereoisomers of α-hydroxymetoprolol, the cellobiohydrolase (CBH) protein based CSP was used. An octadecyl silica based LC column was applied for the separation of diazepam and nordiazepam. The analytes were detected by the use of tandem quadrupole mass spectrometry operating in selective reactive monitoring mode. High resolution MS, employing a quadrupole time-of-flight (QqTOF) mass analyzer, was utilized for the identification of an unknown compound in wastewater samples. The APIs and their metabolites, as well as their respective enantiomers, were quantified in raw and treated wastewater from Uppsala, Sweden along with surface water from the River Fyris in Uppsala.
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| 8. |
- Baumann, Dominik
(författare)
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Learning and Control Strategies for Cyber-physical Systems: From Wireless Control over Deep Reinforcement Learning to Causal Identification
- 2020
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Cyber-physical systems (CPS) integrate physical processes with computing and communication to autonomously interact with the environment. This enables emerging applications such as autonomous driving or smart factories. However, current technology does not provide the dependability and adaptability to realize those applications. CPS are systems with complex dynamics that need to be adaptive, communicate with each other over wireless channels, and provide theoretical guarantees on proper functioning. In this thesis, we take on the challenges imposed by wireless CPS by developing appropriate learning and control strategies.In the first part of the thesis, we present a holistic approach that enables provably stable feedback control over wireless networks. At design time (i.e., prior to execution), we tame typical imperfections inherent in wireless networks, such as communication delays and message loss. The remaining imperfections are then accounted for through feedback control. At run time (i.e., during execution), we let systems reason about communication demands and allocate communication resources accordingly. We provide theoretical stability guarantees and evaluate the approach on a cyber-physical testbed, featuring a multi-hop wireless network supporting multiple cart-pole systems.In the second part, we enhance the flexibility of our designs through learning. We first propose a framework based on deep reinforcement learning to jointly learn control and communication strategies for wireless CPS by integrating both objectives, control performance and saving communication resources, in the reward function. This enables learning of resource-aware controllers for nonlinear and high-dimensional systems. Second, we propose an approach for evaluating the performance of models of wireless CPS through online statistical analysis. We trigger learning in case performance drops, that way limiting the number of learning experiments and reducing computational complexity. Third, we propose an algorithm for identifying the causal structure of control systems. We provide theoretical guarantees on learning the true causal structure and demonstrate enhanced generalization capabilities inherited through causal structure identification on a real robotic system.
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| 9. |
- Belibasakis, Georgios N., 1976-
(författare)
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Cellular and molecular responses of periodontal connective tissue cells to Actinobacillus actinomycetemcomitans cytolethal distending toxin
- 2004
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Actinobacillus actinomycetemcomitans is present in elevated proportions and numbers in dental bacterial biofilms of patients with localized aggressive periodontitis. This variant of periodontal disease, occurring in adolescents and young adults, is characterized by rapid and severe destruction of the connective tissues and bone supporting the teeth, eventually culminating in tooth loss. The cytolethal distending toxin (Cdt) is a newly discovered bacterial protein toxin, uniquely present in A. actinomycetemcomitans among all known to-date oral bacterial species. The Cdt has the capacity to inhibit mammalian cell growth, but its putative role in the pathogenesis of the disease is unclear. The aim of this in vitro work has been to study the effects of A. actinomycetemcomitans on periodontal connective tissue cell cultures, and to evaluate the possible involvement of its Cdt. A. actinomycetemcomitans inhibited the proliferation of gingival and periodontal ligament fibroblasts, as a result of a combined arrest at the G1 and G2/M phases of the cell cycle. This growth inhibition was non-lethal and the cells remained metabolically active, although their DNA synthesis was reduced. The intoxicated cells exhibited increased size and irregular structure, characterized by distension and elongation. This cellular enlargement occurred in both G1 and G2/M phase arrested cells. The Cdt of A. actinomycetemcomitans was responsible for the observed growth inhibition, as well as the concomitant morphological alterations. The possible induction of inflammatory cytokines related to bone resorption was investigated in response to A. actinomycetemcomitans, and the involvement of Cdt was evaluated. Extensive focus was given to the study of receptor activator of NF-κB ligand (RANKL) expression, a membrane-bound ligand that signals osteoclast progenitors to differentiate and fuse into mature osteoclasts, activating bone resorption. It was demonstrated that A. actinomycetemcomitans induced RANKL mRNA and protein expression in the cells studied, but did not affect the expression of its decoy receptor, osteoprotegerin. This induction was solely attributed to its Cdt, as demonstrated by the use of a cdt-knockout A. actinomycetemcomitans strain, purified recombinant Cdt, and antibodies blocking the Cdt. In addition, this event was not mediated by pro-inflammatory cytokines known to stimulate RANKL. Interleukin-6 mRNA and protein expression were also enhanced by A. actinomycetemcomitans, but Cdt had limited involvement in this enhancement. In conclusion, two distinct mechanisms by which A. actinomycetemcomitans Cdt may be involved in the pathogenesis of localized aggressive periodontitis are proposed. Firstly, the growth arrest of the resident fibroblasts may impair the physiological connective tissue remodelling equilibrium and lead to connective tissue attachment loss. Secondly, the induction of RANKL by these cells, residing in the proximity of the alveolar bone, may locally stimulate osteoclastogenesis and promote alveolar bone resorption. This work also provides further insights to the understanding of Cdt mechanisms of action, contributing to the global characterization of the toxin’s virulence.
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| 10. |
- 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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