| 1. |
- Abdalmoaty, Mohamed, 1986-, et al.
(author)
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Noise reduction in Laguerre-domain discrete delay estimation
- 2022
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In: 2022 IEEE 61st Conference on Decision and Control (CDC). - : Institute of Electrical and Electronics Engineers (IEEE). - 9781665467612 - 9781665467605 - 9781665467629 ; , s. 6254-6259
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Conference paper (peer-reviewed)abstract
- This paper introduces a stochastic framework for a recently proposed discrete-time delay estimation method in Laguerre-domain, i.e. with the delay block input and output signals being represented by the corresponding Laguerre series. A novel Laguerre-domain disturbance model allowing the involved signals to be square-summable sequences is devised. The relation to two commonly used time-domain disturbance models is clarified. Furthermore, by forming the input signal in a certain way, the signal shape of an additive output disturbance can be estimated and utilized for noise reduction. It is demonstrated that a significant improvement in the delay estimation error is achieved when the noise sequence is correlated. The noise reduction approach is applicable to other Laguerre-domain problems than pure delay estimation.
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| 2. |
- Bereza-Jarocinski, Robert, et al.
(author)
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Stochastic Approximation for Identification of Non-Linear Differential-Algebraic Equations with Process Disturbances
- 2022
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In: 2022 IEEE 61ST CONFERENCE ON DECISION AND CONTROL (CDC). - : Institute of Electrical and Electronics Engineers (IEEE). - 9781665467612 - 9781665467605 - 9781665467629 ; , s. 6712-6717
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Conference paper (peer-reviewed)abstract
- Differential-algebraic equations, commonly used to model physical systems, are the basis for many equation-based object-oriented modeling languages. When systems described by such equations are influenced by unknown process disturbances, estimating unknown parameters from experimental data becomes difficult. This is because of problems with the existence of well-defined solutions and the computational tractability of estimators. In this paper, we propose a way to minimize a cost function-whose minimizer is a consistent estimator of the true parameters-using stochastic gradient descent. This approach scales significantly better with the number of unknown parameters than other currently available methods for the same type of problem. The performance of the method is demonstrated through a simulation study with three unknown parameters. The experiments show a significantly reduced variance of the estimator, compared to an output error method neglecting the influence of process disturbances, as well as an ability to reduce the estimation bias of parameters that the output error method particularly struggles with.
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| 3. |
- Gräfe, Alexander, et al.
(author)
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Towards remote fault detection by analyzing communication priorities
- 2022
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In: 2022 IEEE 61st Conference on Decision and Control (CDC). - : Institute of Electrical and Electronics Engineers (IEEE). - 9781665467612 - 9781665467605 - 9781665467629 ; , s. 1758-1763
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Conference paper (peer-reviewed)abstract
- The ability to detect faults is an important safety feature for event-based multi-agent systems. In most existing algorithms, each agent tries to detect faults by checking its own behavior. But what if one agent becomes unable to recognize misbehavior, for example due to failure in its onboard fault detection? To improve resilience and avoid propagation of individual errors to the multi-agent system, agents should check each other remotely for malfunction or misbehavior. In this paper, we build upon a recently proposed predictive triggering architecture that involves communication priorities shared throughout the network to manage limited bandwidth. We propose a fault detection method that uses these priorities to detect errors in other agents. The resulting algorithms is not only able to detect faults, but can also run on a low-power microcontroller in real-time, as we demonstrate in hardware experiments.
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| 4. |
- Lapandic, Dzenan, et al.
(author)
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Robust Trajectory Tracking for Underactuated Quadrotors with Prescribed Performance
- 2022
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In: 2022 IEEE 61st Conference on Decision and Control (CDC). - : Institute of Electrical and Electronics Engineers (IEEE). - 9781665467612 - 9781665467605 - 9781665467629 ; , s. 3351-3358
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Conference paper (peer-reviewed)abstract
- We propose a control protocol based on the prescribed performance control (PPC) methodology for a quadro-tor unmanned aerial vehicle (UAV). Quadrotor systems belong to the class of underactuated systems for which the original PPC methodology cannot be directly applied. We introduce the necessary design modifications to stabilize the considered system with prescribed performance. The proposed control protocol does not use any information of dynamic model parameters or exogenous disturbances. Furthermore, the stability analysis guarantees that the tracking errors remain inside of designer-specified time-varying functions, achieving prescribed performance independent from the control gains’ selection. Finally, simulation results verify the theoretical results.
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| 5. |
- Naha, Arunava, et al.
(author)
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Structural analyses of a parsimonious watermarking policy for data deception attack detection in networked control systems
- 2022
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In: 2022 IEEE 61st Conference on Decision and Control (CDC). - : Institute of Electrical and Electronics Engineers (IEEE). - 9781665467612 - 9781665467605 - 9781665467629 ; , s. 7648-7655
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Conference paper (peer-reviewed)abstract
- In this paper, we perform structural analyses of a parsimonious watermarking policy, which minimizes the average detection delay (ADD) to detect data deception attacks on networked control systems (NCS) for a fixed upper bound on the false alarm rate (FAR). The addition of physical watermarking to the control input of a NCS increases the probability of attack detections with an increase in the control cost. Therefore, we formulate the problem of data deception attack detection for NCS with the facility to add physical watermarking as a stochastic optimal control problem. Then we solve the problem by applying dynamic programming value iterations and find a parsimonious watermarking policy that decides to add watermarking and detects attacks based on the estimated posterior probability of attack. We analyze the optimal policy structure and find that it can be a one, two or three threshold policy depending on a few parameter values. Simulation studies show that the optimal policy for a practical range of parameter values is a two-threshold policy on the posterior probability of attack. Derivation of a threshold-based policy from the structural analysis of the value iteration method reduces the computational complexity during the runtime implementation and offers better structural insights. Furthermore, such an analysis provides a guideline for selecting the parameter values to meet the design requirements.
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| 6. |
- Nguyen, Anh Tung, et al.
(author)
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A Zero-Sum Game Framework for Optimal Sensor Placement in Uncertain Networked Control Systems under Cyber-Attacks
- 2022
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In: 2022 IEEE 61st Conference on Decision and Control (CDC). - : Institute of Electrical and Electronics Engineers (IEEE). - 9781665467629 - 9781665467612 - 9781665467605 ; , s. 6126-6133
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Conference paper (peer-reviewed)abstract
- This paper proposes a game-theoretic approach to address the problem of optimal sensor placement against an adversary in uncertain networked control systems. The problem is formulated as a zero-sum game with two players, namely a malicious adversary and a detector. Given a protected performance vertex, we consider a detector, with uncertain system knowledge, that selects another vertex on which to place a sensor and monitors its output with the aim of detecting the presence of the adversary. On the other hand, the adversary, also with uncertain system knowledge, chooses a single vertex and conducts a cyber-attack on its input. The purpose of the adversary is to drive the attack vertex as to maximally disrupt the protected performance vertex while remaining undetected by the detector. As our first contribution, the game payoff of the above-defined zero-sum game is formulated in terms of the Value-at-Risk of the adversary’s impact. However, this game payoff corresponds to an intractable optimization problem. To tackle the problem, we adopt the scenario approach to approximately compute the game payoff. Then, the optimal monitor selection is determined by analyzing the equilibrium of the zero-sum game. The proposed approach is illustrated via a numerical example of a 10-vertex networked control system.
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| 7. |
- Cederberg, Daniel, et al.
(author)
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Synthesis of Minimax Adaptive Controller for a Finite Set of Linear Systems
- 2022
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In: 2022 IEEE 61ST CONFERENCE ON DECISION AND CONTROL (CDC). - : IEEE. - 2576-2370 .- 0743-1546. - 9781665467612 - 9781665467629 ; , s. 1380-1384
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Conference paper (peer-reviewed)abstract
- The design of an adaptive controller with bounded L-2-gain from disturbances to errors for linear time-invariant systems with uncertain parameters restricted to a finite set is investigated. The synthesis of the controller requires finding matrices satisfying non-convex matrix inequalities. We propose an approach for finding these matrices based on repeatedly linearizing the terms that cause the non-convexity of the inequalities. Empirical evidence suggests that the approach leads to adaptive controllers with significantly smaller upper bound on the L-2-gain.
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| 8. |
- Shoja, Shamisa, Biträdande professor, 1991-, et al.
(author)
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Exact Complexity Certification of a Standard Branch and Bound Method for Mixed-Integer Linear Programming
- 2022
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In: Proceedings of 2022 Conference on Decision and Control (CDC). - : Institute of Electrical and Electronics Engineers (IEEE). - 9781665467629 - 9781665467612 ; , s. 6298-6305
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Conference paper (peer-reviewed)abstract
- Model predictive control (MPC) with linear cost function for hybrid systems requires the solution of a mixed-integer linear program (MILP) at each sampling time. The branch and bound (B&B) method is a commonly used tool for solving mixed-integer problems. In this work, we present an algorithm to exactly certify the computational complexity of a standard B&B-based MILP solver. By the proposed method, guarantees on worst-case complexity bounds, e.g., the worst-case iterations or size of the B&B tree, are provided. This knowledge is a fundamental requirement for the implementation of MPC in a real-time system. Different node selection strategies, including best-first, are considered when certifying the complexity of the B&B method. Furthermore, the proposed certification algorithm is extended to consider warm-starting of the inner solver in the B&B. We illustrate the usefulness of the proposed algorithm by comparing against the corresponding online MILP solver in numerical experiments using both cold-started and warm-started LP solvers.
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| 9. |
- Wang, Lingfei, et al.
(author)
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A social power game for the concatenated Friedkin-Johnsen model
- 2022
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In: 2022 IEEE 61ST CONFERENCE ON DECISION AND CONTROL (CDC). - : IEEE. - 9781665467612 - 9781665467629 ; , s. 3513-3518
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Conference paper (peer-reviewed)abstract
- If a concatenated Friedkin-Johnsen model is used to describe the evolution of the opinions of stubborn agents in a sequence of discussion events, then the social power achieved by the agents at the end of the discussions depends from the stubbornness coefficients adopted by the agents through the sequence of events. In this paper we assume that the agents are free to choose their stubbornness profiles, and ask ourselves what strategy should an agent follow in order to maximize its social power. Formulating the problem as a strategic game, we show that choosing the highest possible values of stubbornness in the early discussions leads to the highest possible social power.
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| 10. |
- Alutto, Martina, et al.
(author)
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Multiple peaks in network SIR epidemic models
- 2022
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In: 2022 IEEE 61st Conference on Decision and Control, CDC 2022. - 2576-2370 .- 0743-1546. - 9781665467612 ; 2022-December, s. 5614-5619
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Conference paper (peer-reviewed)abstract
- We study network SIR (Susceptible - Infected - Recovered) epidemic models in the case of two interacting populations. We analyze the dynamics behavior of the fractions of infected individuals in the two populations. In contrast to the classical scalar SIR epidemic model, where the fraction of infected individuals is known to have an unimodal behavior (either decreasing throughout time or initially increasing, until reaching a peak and decreasing everafter), we show the possible occurrence of a novel multimodal behaviors in the network SIR model. Specifically, we show that the curve of the fraction of infected individuals in a population may incur in a change of monotonicity even when it starts with a decreasing trend. Our analysis focuses on a homogeneous mixing model, whereby all contacts have unitary frequency. We study the initial conditions and network characteristics sufficient for the aforementioned multimodal behavior to emerge and those that instead guarantee the classical unimodal behavior.
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