arXiv subjects

Henrik Sandberg

Publications and source records attributed to Henrik Sandberg.

At least 127 records · Page 7Linked to original sources

arXiv2015

SDP-based Joint Sensor and Controller Design for Information-regularized Optimal LQG Control

We consider a joint sensor and controller design problem for linear Gaussian stochastic systems in which a weighted sum of quadratic control cost and the amount of information acquired by the sensor is minimized. This problem formulation is motivated by situations where a control law must be designed in the presence of sensing, communication, and privacy constraints. We show that the optimal joint sensor-controller design is relatively easy when the sensing policy is restricted to be linear. Namely, an explicit form of the optimal linear sensor equation, the Kalman filter, and the certainty equivalence controller that jointly solves the problem can be efficiently found by semidefinite programming (SDP). Whether the linearity assumption in our design is restrictive or not is currently an open problem.

math.OC↗

arXiv2015

Multiple Loop Self-Triggered Model Predictive Control for Network Scheduling and Control

We present an algorithm for controlling and scheduling multiple linear time-invariant processes on a shared bandwidth limited communication network using adaptive sampling intervals. The controller is centralized and computes at every sampling instant not only the new control command for a process, but also decides the time interval to wait until taking the next sample. The approach relies on model predictive control ideas, where the cost function penalizes the state and control effort as well as the time interval until the next sample is taken. The latter is introduced in order to generate an adaptive sampling scheme for the overall system such that the sampling time increases as the norm of the system state goes to zero. The paper presents a method for synthesizing such a predictive controller and gives explicit sufficient conditions for when it is stabilizing. Further explicit conditions are given which guarantee conflict free transmissions on the network. It is shown that the optimization problem may be solved off-line and that the controller can be implemented as a lookup table of state feedback gains. Simulation studies which compare the proposed algorithm to periodic sampling illustrate potential performance gains.

eess.SY↗

arXiv2014

Optimal scaling of the ADMM algorithm for distributed quadratic programming

This paper presents optimal scaling of the alternating directions method of multipliers (ADMM) algorithm for a class of distributed quadratic programming problems. The scaling corresponds to the ADMM step-size and relaxation parameter, as well as the edge-weights of the underlying communication graph. We optimize these parameters to yield the smallest convergence factor of the algorithm. Explicit expressions are derived for the step-size and relaxation parameter, as well as for the corresponding convergence factor. Numerical simulations justify our results and highlight the benefits of optimally scaling the ADMM algorithm.

math.OC↗

arXiv2014

SiMpLIfy: A Toolbox for Structured Model Reduction

In this paper, we present a toolbox for structured model reduction developed for MATLAB. In addition to structured model reduction methods using balanced realizations of the subsystems, we introduce a numerical algorithm for structured model reduction using a subgradient optimization algorithm. We briefly present the syntax for the toolbox and its features. Finally, we demonstrate the applicability of various model reduction methods in the toolbox on a structured mass-spring mechanical system.

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arXiv2014

Distributed PI-Control with Applications to Power Systems Frequency Control

This paper considers a distributed PI-controller for networked dynamical systems. Sufficient conditions for when the controller is able to stabilize a general linear system and eliminate static control errors are presented. The proposed controller is applied to frequency control of power transmission systems. Sufficient stability criteria are derived, and it is shown that the controller parameters can always be chosen so that the frequencies in the closed loop converge to nominal operational frequency. We show that the load sharing property of the generators is maintained, i.e., the input power of the generators is proportional to a controller parameter. The controller is evaluated by simulation on the IEEE 30 bus test network, where its effectiveness is demonstrated.

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arXiv2014

Distributed Voltage and Current Control of Multi-Terminal High-Voltage Direct Current Transmission Systems

High-voltage direct current (HVDC) is a commonly used technology for long-distance power transmission, due to its low resistive losses and low costs. In this paper, a novel distributed controller for multi-terminal HVDC (MTDC) systems is proposed. Under certain conditions on the controller gains, it is shown to stabilize the MTDC system. The controller is shown to always keep the voltages close to the nominal voltage, while assuring that the injected power is shared fairly among the converters. The theoretical results are validated by simulations, where the affect of communication time-delays is also studied.

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arXiv2014

Distributed Control of Networked Dynamical Systems: Static Feedback, Integral Action and Consensus

This paper analyzes distributed control protocols for first- and second-order networked dynamical systems. We propose a class of nonlinear consensus controllers where the input of each agent can be written as a product of a nonlinear gain, and a sum of nonlinear interaction functions. By using integral Lyapunov functions, we prove the stability of the proposed control protocols, and explicitly characterize the equilibrium set. We also propose a distributed proportional-integral (PI) controller for networked dynamical systems. The PI controllers successfully attenuate constant disturbances in the network. We prove that agents with single-integrator dynamics are stable for any integral gain, and give an explicit tight upper bound on the integral gain for when the system is stable for agents with double-integrator dynamics. Throughout the paper we highlight some possible applications of the proposed controllers by realistic simulations of autonomous satellites, power systems and building temperature control.

math.DS↗

arXiv2014

Second-law-like inequalities with information and their interpretations

In a thermodynamic process with measurement and feedback, the second law of thermodynamics is no longer valid. In its place, various second-law-like inequalities have been advanced that each incorporate a distinct additional term accounting for the information gathered through measurement. We quantitatively compare a number of these information measures using an analytically tractable model for the feedback cooling of a Brownian particle. We find that the information measures form a hierarchy that reveals a web of interconnections. To untangle their relationships, we address the origins of the information, arguing that each information measure represents the minimum thermodynamic cost to acquire that information through a separate, distinct measurement protocol.

cond-mat.stat-mech↗

arXiv2014

Maximum work extraction and implementation costs for non-equilibrium Maxwell's demons

In this theoretical study, we determine the maximum amount of work extractable in finite time by a demon performing continuous measurements on a quadratic Hamiltonian system subjected to thermal fluctuations, in terms of the information extracted from the system. This is in contrast to many recent studies that focus on demons' maximizing the extracted work over received information, and operate close to equilibrium. The maximum work demon is found to apply a high-gain continuous feedback using a Kalman-Bucy estimate of the system state. A simple and concrete electrical implementation of the feedback protocol is proposed, which allows for analytic expressions of the flows of energy and entropy inside the demon. This let us show that any implementation of the demon must necessarily include an external power source, which we prove both from classical thermodynamics arguments and from a version of Landauer's memory erasure argument extended to non-equilibrium linear systems.

cond-mat.stat-mech↗

arXiv2014

Model reduction of networked passive systems through clustering

In this paper, a model reduction procedure for a network of interconnected identical passive subsystems is presented. Here, rather than performing model reduction on the subsystems, adjacent subsystems are clustered, leading to a reduced-order networked system that allows for a convenient physical interpretation. The identification of the subsystems to be clustered is performed through controllability and observability analysis of an associated edge system and it is shown that the property of synchronization (i.e., the convergence of trajectories of the subsystems to each other) is preserved during reduction. The results are illustrated by means of an example.

eess.SY↗

arXiv2014

Performance Analysis of a Network of Event-based Systems

We consider a scenario where multiple event-based systems use a wireless network to communicate with their respective controllers. These systems use a contention resolution mechanism (CRM) to arbitrate access to the network. We present a Markov model for the network interactions between the event-based systems. Using this model, we obtain an analytical expression for the reliability, or the probability of successfully transmitting a packet, in this network. There are two important aspects to our model. Firstly, our model captures the joint interactions of the event-triggering policy and the CRM. This is required because event-triggering policies typically adapt to the CRM outcome. Secondly, the model is obtained by decoupling interactions between the different systems in the network, drawing inspiration from Bianchi's analysis of IEEE 802.11. This is required because the network interactions introduce a correlation between the system variables. We present Monte-Carlo simulations that validate our model under various network configurations, and verify our performance analysis as well.

eess.SY↗

arXiv2014

Stability Analysis and Design of a Network of Event-based Systems

We consider a network of event-based systems that use a shared wireless medium to communicate with their respective controllers. These systems use a contention resolution mechanism to arbitrate access to the shared network. We identify sufficient conditions for Lyapunov mean square stability of each control system in the network, and design event-based policies that guarantee it. Our stability analysis is based on a Markov model that removes the network-induced correlation between the states of the control systems in the network. Analyzing the stability of this Markov model remains a challenge, as the event-triggering policy renders the estimation error non-Gaussian. Hence, we identify an auxiliary system that furnishes an upper bound for the variance of the system states. Using the stability analysis, we design policies, such as the constant-probability policy, for adapting the event-triggering thresholds to the delay in accessing the network. Realistic wireless networked control examples illustrate the applicability of the presented approach.

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arXiv2013

Finite-time thermodynamics of port-Hamiltonian systems

In this paper, we identify a class of time-varying port-Hamiltonian systems that is suitable for studying problems at the intersection of statistical mechanics and control of physical systems. Those port-Hamiltonian systems are able to modify their internal structure as well as their interconnection with the environment over time. The framework allows us to prove the First and Second laws of thermodynamics, but also lets us apply results from optimal and stochastic control theory to physical systems. In particular, we show how to use linear control theory to optimally extract work from a single heat source over a finite time interval in the manner of Maxwell's demon. Furthermore, the optimal controller is a time-varying port-Hamiltonian system, which can be physically implemented as a variable linear capacitor and transformer. We also use the theory to design a heat engine operating between two heat sources in finite-time Carnot-like cycles of maximum power, and we compare those two heat engines.

cond-mat.stat-mech↗

arXiv2013

Optimal H-infinity Control Design under Model Information Limitations and State Measurement Constraints

We present a suboptimal control design algorithm for a family of continuous-time parameter-dependent linear systems that are composed of interconnected subsystems. We are interested in designing the controller for each subsystem such that it only utilizes partial state measurements (characterized by a directed graph called the control graph) and limited model parameter information (characterized by the design graph). The algorithm is based on successive local minimizations and maximizations (using the subgradients) of the $H_\infty$--norm of the closed-loop transfer function with respect to the controller gains and the system parameters. We use a vehicle platooning example to illustrate the applicability of the results.

math.OC↗

arXiv2013

Efficient Computations of a Security Index for False Data Attacks in Power Networks

The resilience of Supervisory Control and Data Acquisition (SCADA) systems for electric power networks for certain cyber-attacks is considered. We analyze the vulnerability of the measurement system to false data attack on communicated measurements. The vulnerability analysis problem is shown to be NP-hard, meaning that unless $P = NP$ there is no polynomial time algorithm to analyze the vulnerability of the system. Nevertheless, we identify situations, such as the full measurement case, where it can be solved efficiently. In such cases, we show indeed that the problem can be cast as a generalization of the minimum cut problem involving costly nodes. We further show that it can be reformulated as a standard minimum cut problem (without costly nodes) on a modified graph of proportional size. An important consequence of this result is that our approach provides the first exact efficient algorithm for the vulnerability analysis problem under the full measurement assumption. Furthermore, our approach also provides an efficient heuristic algorithm for the general NP-hard problem. Our results are illustrated by numerical studies on benchmark systems including the IEEE 118-bus system.

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arXiv2012

A Secure Control Framework for Resource-Limited Adversaries

Cyber-secure networked control is modeled, analyzed, and experimentally illustrated in this paper. An attack space defined by the adversary's system knowledge, disclosure, and disruption resources is introduced. Adversaries constrained by these resources are modeled for a networked control system architecture. It is shown that attack scenarios corresponding to denial-of-service, replay, zero-dynamics, and bias injection attacks can be analyzed using this framework. Furthermore, the attack policy for each scenario is described and the attack's impact is characterized using the concept of safe sets. An experimental setup based on a quadruple-tank process controlled over a wireless network is used to illustrate the attack scenarios, their consequences, and potential counter-measures.

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arXiv2012

Complexity Reduction for Parameter-Dependent Linear Systems

We present a complexity reduction algorithm for a family of parameter-dependent linear systems when the system parameters belong to a compact semi-algebraic set. This algorithm potentially describes the underlying dynamical system with fewer parameters or state variables. To do so, it minimizes the distance (i.e., H-infinity-norm of the difference) between the original system and its reduced version. We present a sub-optimal solution to this problem using sum-of-squares optimization methods. We present the results for both continuous-time and discrete-time systems. Lastly, we illustrate the applicability of our proposed algorithm on numerical examples.

eess.SY↗

arXiv2012

On the Exact Solution to a Smart Grid Cyber-Security Analysis Problem

This paper considers a smart grid cyber-security problem analyzing the vulnerabilities of electric power networks to false data attacks. The analysis problem is related to a constrained cardinality minimization problem. The main result shows that an $l_1$ relaxation technique provides an exact optimal solution to this cardinality minimization problem. The proposed result is based on a polyhedral combinatorics argument. It is different from well-known results based on mutual coherence and restricted isometry property. The results are illustrated on benchmarks including the IEEE 118-bus and 300-bus systems.

math.OC↗