| 1. |
- Flärdh, Oscar, 1980-
(författare)
-
Modelling, analysis and experimentation of a simple feedback scheme for error correction control
- 2007
-
Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Data networks are an important part in an increasing number of applications with real-time and reliability requirements. To meet these demands a variety of approaches have been proposed. Forward error correction, which adds redundancy to the communicated data, is one of them. However, the redundancy occupies communication bandwidth, so it is desirable to control the amount of redundancy in order to achieve high reliability without adding excessive communication delay. The main contribution of the thesis is to formulate the problem of adjusting the redundancy in a control framework, which enables the dynamic properties of error correction control to be analyzed using control theory. The trade-off between application quality and resource usage is captured by introducing an optimal control problem. Its dependence on the knowledge of the network state at the transmission side is discussed. An error correction controller that optimizes the amount of redundancy without relying on network state information is presented. This is achieved by utilizing an extremum seeking control algorithm to optimize the cost function. Models with varying complexity of the resulting feedback system are presented and analyzed. Conditions for convergence are given. Multiple-input describing function analysis is used to examine periodic solutions. The results are illustrated through computer simulations and experiments on a wireless sensor network.
|
|
| 2. |
- Adaldo, Antonio, 1989-
(författare)
-
Event-triggered control of multi-agent systems: pinning control, cloud coordination, and sensor coverage
- 2016
-
Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- A multi-agent system is composed of interconnected subsystems, or agents. In control of multi-agent systems, the aim is to obtain a coordinated behavior of the overall system through local interactions among the agents. Communication among the agents often occurs over a wireless medium with finite capacity. In this thesis, we investigate multiagent control systems where inter-agent communication is modelled by discrete events triggered by state conditions.In the first part, we consider event-triggered pinning control for a network of agents with nonlinear dynamics and time-varying topologies. Pinning control is a strategy to steer the behavior of a multi-agent 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.In the second part, we propose a control algorithm for multi-agent systems where inter-agent communication is substituted with a shared remote repository hosted on a cloud. Communication between each agent and the cloud is modelled 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 finite time interval.In the third part, we propose a family of distributed algorithms for coverage and inspection tasks for a network of mobile sensors with asymmetric footprints. 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 sensor network attains nondecreasing coverage, and we characterize the equilibrium configurations. The results presented in the thesis are corroborated by simulations or experiments.
|
|
| 3. |
- Aguiar, Miguel
(författare)
-
Learning flow functions : architectures, universal approximation and applications to spiking systems
- 2024
-
Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Learning flow functions of continuous-time control systems is considered in this thesis. The flow function is the operator mapping initial states and control inputs to the state trajectories, and the problem is to find a suitable neural network architecture to learn this infinite-dimensional operator from measurements of state trajectories. The main motivation is the construction of continuous-time simulation models for such systems. The contribution is threefold.We first study the design of neural network architectures for this problem, when the control inputs have a certain discrete-time structure, inspired by the classes of control inputs commonly used in applications. We provide a mathematical formulation of the problem and show that, under the considered input class, the flow function can be represented exactly in discrete time. Based on this representation, we propose a discrete-time recurrent neural network architecture. We evaluate the architecture experimentally on data from models of two nonlinear oscillators, namely the Van der Pol oscillator and the FitzHugh-Nagumo oscillator. In both cases, we show that we can train models which closely reproduce the trajectories of the two systems.Secondly, we consider an application to spiking systems. Conductance-based models of biological neurons are the prototypical examples of this type of system. Because of their multi-timescale dynamics and high-frequency response, continuous-time representations which are efficient to simulate are desirable. We formulate a framework for surrogate modelling of spiking systems from trajectory data, based on learning the flow function of the system. The framework is demonstrated on data from models of a single biological neuron and of the interconnection of two neurons. The results show that we are able to accurately replicate the spiking behaviour.Finally, we prove an universal approximation theorem for the proposed recurrent neural network architecture. First, general conditions are given on the flow function and the control inputs which guarantee that the architecture is able to approximate the flow function of any control system with arbitrary accuracy. Then, we specialise to systems with dynamics given by a controlled ordinary differential equation, showing that the conditions are satisfied whenever the equation has a continuously differentiable right-hand side, for the control input classes of interest.
|
|
| 4. |
- Alisic, Rijad, 1994-
(författare)
-
Privacy of Sudden Events in Cyber-Physical Systems
- 2021
-
Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Cyberattacks against critical infrastructures has been a growing problem for the past couple of years. These infrastructures are a particularly desirable target for adversaries, due to their vital importance in society. For instance, a stop in the operation of a critical infrastructure could result in a crippling effect on a nation's economy, security or public health. The reason behind this increase is that critical infrastructures have become more complex, often being integrated with a large network of various cyber components. It is through these cyber components that an adversary is able to access the system and conduct their attacks.In this thesis, we consider methods which can be used as a first line of defence against such attacks for Cyber-Physical Systems (CPS). Specifically, we start by studying how information leaks about a system's dynamics helps an adversary to generate attacks that are difficult to detect. In many cases, such attacks can be detrimental to a CPS since they can drive the system to a breaking point without being detected by the operator that is tasked to secure the system. We show that an adversary can use small amounts of data procured from information leaks to generate these undetectable attacks. In particular, we provide the minimal amount of information that is needed in order to keep the attack hidden even if the operator tries to probe the system for attacks. We design defence mechanisms against such information leaks using the Hammersley-Chapman-Robbins lower bound. With it, we study how information leakage could be mitigated through corruption of the data by injection of measurement noise. Specifically, we investigate how information about structured input sequences, which we call events, can be obtained through the output of a dynamical system and how this leakage depends on the system dynamics. For example, it is shown that a system with fast dynamical modes tends to disclose more information about an event compared to a system with slower modes. However, a slower system leaks information over a longer time horizon, which means that an adversary who starts to collect information long after the event has occured might still be able to estimate it. Additionally, we show how sensor placements can affect the information leak. These results are then used to aid the operator to detect privacy vulnerabilities in the design of a CPS.Based on the Hammersley-Chapman-Robbins lower bound, we provide additional defensive mechanisms that can be deployed by an operator online to minimize information leakage. For instance, we propose a method to modify the structured inputs in order to maximize the usage of the existing noise in the system. This mechanism allows us to explicitly deal with the privacy-utility trade-off, which is of interest when optimal control problems are considered. Finally, we show how the adversary's certainty of the event increases as a function of the number of samples they collect. For instance, we provide sufficient conditions for when their estimation variance starts to converge to its final value. This information can be used by an operator to estimate when possible attacks from an adversary could occur, and change the CPS before that, rendering the adversary's collected information useless.
|
|
| 5. |
- Andreasson, Martin, 1987-
(författare)
-
Control of Multi-Agent Systems with Applications to Distributed Frequency Control Power Systems
- 2013
-
Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Multi-agent systems are interconnected control systems with many application domains. The first part of this thesis considers nonlinear multi-agent systems, where the control input can be decoupled into a product of a nonlinear gain function depending only on the agent's own state, and a nonlinear interaction function depending on the relative states of the agent's neighbors. We prove stability of the overall system, and explicitly characterize the equilibrium state for agents with both single- and double-integrator dynamics.Disturbances may seriously degrade the performance of multi-agent systems. Even constant disturbances will in general cause the agents to diverge, rather than to converge, for many control protocols. In the second part of this thesis we introduce distributed proportional-integral controllers to attenuate constant disturbances in multi-agent systems with first- and second-order dynamics. We derive explicit stability criteria based on the integral gain of the controllers.Lastly, this thesis presents both centralized and distributed frequency controllers for electrical power transmission systems. Based on the theory developed for multi-agent systems, a decentralized controller regulating the system frequencies under load changes is proposed. An optimal distributed frequency controller is also proposed, which in addition to regulating the frequencies to the nominal frequency, minimizes the cost of power generation.
|
|
| 6. |
- Björk, Joakim, 1989-
(författare)
-
Performance Quantification of Interarea Oscillation Damping Using HVDC
- 2019
-
Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- With the transition towards renewable energy, and the deregulation of the electricity market, generation patterns and grid topology are changing. These changes increase the need for transfer capacity. One limiting factor, which sometimes leads to underutilization of the transmission grid, is interarea oscillations. These system-wide modes involve groups of generators oscillating relative to each other and are sometimes hard to control due to their scale and complexity. In this thesis we investigate how high-voltage direct current (HVDC) transmission can be used to attenuate interarea oscillations. The thesis has two main contributions.In the first contribution we show how the stability of two asynchronous grids can be improved by modulating the active power of a single interconnecting HVDC link. One concern 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 always possible to improve the damping in both grids as long as the frequencies of their interarea modes are not too close. For simplified models, it is explicitly shown how the controllability, and therefore the achievable damping improvements, deteriorates as the frequency difference becomes small.The second contribution of the thesis is to show how coordinated control of two (or more) links can be used to avoid interaction between troublesome interarea modes. We investigate the performance of some multivariable control designs. In particular we look at input usage as well as robustness to measurement, communication, and actuator failures. Suitable controllers are thereby characterized.
|
|
| 7. |
- Čičić, Mladen, 1991-
(författare)
-
Control of vehicle platoons and traffic dynamics : catch-up coordination and congestion dissipation
- 2019
-
Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Traffic congestion is a constantly growing problem, with a wide array ofnegative effects on the society, from wasted time and productivity to elevated air pollution and increased number of accidents. Classical traffic control methods have long been successfully employed to alleviate congestion, improving the traffic situation of many cities and highways. However, traffic control is not universally employed, because of the necessity of installing additional equipment and instating new legislation. The introduction of connected, autonomous vehicles offers new opportunities for sensing and controlling the traffic. The data that most of the vehicles nowadays provide are already widely used to measure the traffic conditions. It is natural to consider how vehicles could also be used as actuators, driving them in a specific way so that they affect the traffic positively. However, many of the currently considered strategies for congestion reduction using autonomous vehicles rely on having a high penetration rate, which is not likely to be the case in the near future. This raises the question: How can we influence the overall traffic by using only a small portion of vehicles that we have direct control over? There are two problems in particular that this thesis considers, congestion wave dissipation and avoidance, and platoon catch-up coordination.First, we study how to dissipate congestion waves by use of a directly controlled vehicle acting as a moving bottleneck. Traffic data can help predict disturbances and constraints that the vehicle will face, and the individual vehicles can be actuated to improve the overall traffic situation. We extend the classical cell transmission model to include the influence of a moving bottleneck, and then use this model to devise a control strategy for an actuator vehicle. By employing such control, we are able to homogenize the traffic without significantly reducing throughput. Under realistic conditions, it is shown that the average total variation of traffic density can be reduced over 5%, while the total travel time increases only 1%.Second, we study how to predict and control vehicles catching up in order to form a platoon, while driving in highway traffic. The influences of road grade and background traffic are examined and vehicles attempting to form a platoon are modelled as moving bottlenecks. Using this model, we are able to predict how much the vehicles might be delayed because of congestion and adjust the plan accordingly, calculating the optimal platoon catch-up speeds for the vehicles by minimizing their energy consumption. This leads to a reduction of energy cost of up to 0.5% compared to the case when we ignore the traffic conditions. More importantly, we are able to predict when attemptingto form a platoon will result in no energy savings, with approximately 80% accuracy.
|
|
| 8. |
- Gao, Yulong
(författare)
-
Stochastic Invariance and Aperiodic Control for Uncertain Constrained Systems
- 2018
-
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.
|
|
| 9. |
- Iwaki, Takuya, 1986-
(författare)
-
Wireless Sensor Network Scheduling and Event-based Control for Industrial Processes
- 2018
-
Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Control over wireless sensor and actuator networks is of growing interest in process industry since it enables flexible design, deployment, operation, and maintenance. An important problem in industrial wireless control is how to limit the amount of information that needs to be exchanged over the network. In this thesis, network scheduling and remote control co-design is considered to address this problem.In the first part, we propose a design of an optimal network schedule for state estimation over a multi-hop wireless sensor network. We formulate an optimization problem, minimizing a linear combination of the averaged estimation error and transmission energy. A periodic network schedule is obtained, which specifies when and through which routes each sensor in the network should transmit its measurement, so that an optimal remote estimate under sensor energy consideration is achieved. We also propose some suboptimal schedules to reduce the computational load. The effectiveness of the suboptimal schedules is evaluated in numerical examples.In the second part, we propose a co-design framework for sensor scheduling, routing, and control over a multi-hop wireless sensor and actuator network. For a decoupled plant and LQG control performance, we formulate an optimization problem and show that the optimal schedule, routing, and control can be obtained locally for each control loop. In this part, we also introduce algorithms to reconfigure the schedules and routes when a link in the network is disconnected. The results are illustrated in a numerical example.In the third part, we consider event-based feedforward control from a wireless disturbance sensor. We derive stability conditions when the closed-loop system is subject to actuator saturation. Feedforward control with anti-windup compensation is introduced to reduce the effect of actuator saturation. The effectiveness of the approach is illustrated in some numerical examples.
|
|
| 10. |
|
|
