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  • Journal article
    Cao W, Wu J, Jenkins N, Wang C, Green Tet al., 2015,

    Benefits analysis of Soft Open Points for electrical distribution network operation

    , Applied Energy, Vol: 165, Pages: 36-47, ISSN: 1872-9118

    Soft Open Points (SOPs) are power electronic devices installed in place of normally-open points in electrical power distribution networks. They are able to provide active power flow control, reactive power compensation and voltage regulation under normal network operating conditions, as well as fast fault isolation and supply restoration under abnormal conditions. A steady state analysis framework was developed to quantify the operational benefits of a distribution network with SOPs under normal network operating conditions. A generic power injection model was developed and used to determine the optimal SOP operation using an improved Powell’s Direct Set method. Physical limits and power losses of the SOP device (based on back to back voltage-source converters) were considered in the model. Distribution network reconfiguration algorithms, with and without SOPs, were developed and used to identify the benefits of using SOPs. Test results on a 33-bus distribution network compared the benefits of using SOPs, traditional network reconfiguration and the combination of both. The results showed that using only one SOP achieved a similar improvement in network operation compared to the case of using network reconfiguration with all branches equipped with remotely controlled switches. A combination of SOP control and network reconfiguration provided the optimal network operation.
  • Journal article
    Suardi A, Longo S, Kerrigan EC, Constantinides GAet al., 2015,

    Explicit MPC: hard constraint satisfaction under low precision arithmetic

    , Control Engineering Practice, Vol: 47, Pages: 60-69, ISSN: 1873-6939

    MPC is becoming increasingly implemented on embedded systems, where low precision computation is preferred either to reduce costs, speedup execution or reduce power consumption. However, in a low precision implementation, constraint satisfaction cannot be guaranteed. To enforce constraint satisfaction under numerical errors, we adopt tools from forward error analysis to compute an error bound on the output of the embedded controller. We treat this error as a state disturbance and use it to inform the design of a constraint-tightening robust controller. The technique is validated via a practical implementation on an FPGA evaluation board.
  • Journal article
    Ramirez PJ, Papadaskalopoulos D, Strbac G, 2015,

    Co-Optimization of Generation Expansion Planning and Electric Vehicles Flexibility

    , IEEE Transactions on Smart Grid, Vol: 7, Pages: 1609-1619, ISSN: 1949-3061

    The envisaged de-carbonization of power systems poses unprecedented challenges enhancing the potential of flexible demand. However, the incorporation of the latter in system planning has yet to be comprehensively investigated. This paper proposes a novel planning model that allows co-optimizing the investment and operating costs of conventional generation assets and demand flexibility, in the form of smart-charging/discharging electric vehicles (EV). The model includes a detailed representation of EV operational constraints along with the generation technical characteristics, and accounts for the costs required to enable demand flexibility. Computational tractability is achieved through clustering generation units and EV, which allows massively reducing the number of decision variables and constraints, and avoiding non-linearities. Case studies in the context of the U.K. demonstrate the economic value of EV flexibility in reducing peak demand levels and absorbing wind generation variability, and the dependence of this value on the required enabling cost and users' traveling patterns.
  • Journal article
    Cao W, Wu J, Jenkins N, Wang C, Green Tet al., 2015,

    Operating principle of Soft Open Points for electrical distribution network operation

    , Applied Energy, Vol: 164, Pages: 245-257, ISSN: 1872-9118

    Soft Open Points (SOPs) are power electronic devices installed in place of normally-open points in electrical power distribution networks. They are able to provide active power flow control, reactive power compensation and voltage regulation under normal network operating conditions, as well as fast fault isolation and supply restoration under abnormal conditions. Two control modes were developed for the operation of an SOP, using back-to-back voltage-source converters (VSCs). A power flow control mode with current control provides independent control of real and reactive power. A supply restoration mode with a voltage controller enables power supply to isolated loads due to network faults. The operating principle of the back-to-back VSCs based SOP was investigated under both normal and abnormal network operating conditions. Studies on a two-feeder medium-voltage distribution network showed the performance of the SOP under different network-operating conditions: normal, during a fault and post-fault supply restoration. During the change of network operating conditions, a mode switch method based on the phase locked loop controller was used to achieve the transitions between the two control modes. Hard transitions by a direct mode switching were noticed unfavourable, but seamless transitions were obtained by deploying a soft cold load pickup and voltage synchronization process.
  • Conference paper
    Kerrigan EC, Constantinides GA, Suardi A, Picciau A, Khusainov Bet al., 2015,

    Computer Architectures to Close the Loop in Real-time Optimization

    , 54th IEEE Conference on Decision and Control, Publisher: IEEE, Pages: 4597-4611

    Many modern control, automation, signal processing and machine learning applications rely on solving a sequence of optimization problems, which are updated with measurements of a real system that evolves in time. The solutions of each of these optimization problems are then used to make decisions, which may be followed by changing some parameters of the physical system, thereby resulting in a feedback loop between the computing and the physical system. Real-time optimization is not the same as `fast' optimization, due to the fact that the computation is affected by an uncertain system that evolves in time. The suitability of a design should therefore not be judged from the optimality of a single optimization problem, but based on the evolution of the entire cyber-physical system. The algorithms and hardware used for solving a single optimization problem in the office might therefore be far from ideal when solving a sequence of real-time optimization problems. Instead of there being a single, optimal design, one has to trade-off a number of objectives, including performance, robustness, energy usage, size and cost. We therefore provide here a tutorial introduction to some of the questions and implementation issues that arise in real-time optimization applications. We will concentrate on some of the decisions that have to be made when designing the computing architecture and algorithm and argue that the choice of one informs the other.
  • Conference paper
    Liu C, Jaimoukha I, 2015,

    The Computation of Full-complexity Polytopic Robust Control Invariant Sets

    , 54th Conference on Decision and Control, Publisher: IEEE, Pages: 6233-6238

    This paper considers the problem of evaluating robust control invariant (RCI) sets for linear discrete-time systems subject to state and input constraints as well as additive disturbances. An RCI set has the property that if the system state is inside the set at any one time, then it is guaranteed to remain in the set for all future times using a pre-defined state feedback control law. This problem is important in many control applications. We present a numerically efficient algorithm for the computation of full-complexity polytopic RCI sets. Farkas' Theorem is first used to derive necessary and sufficient conditions for the existence of an admissible polytopic RCI set in the form of nonlinear matrix inequalities. An Elimination Lemma is then used to derive sufficient conditions, in the form of linear matrix inequalities, for the existence of the solution. An optimization algorithm to approximate maximal RCI sets is also proposed. Numerical examples are given to illustrate the effectiveness of the proposed algorithm.
  • Conference paper
    Padoan A, Astolfi A, 2015,

    Towards deterministic subspace identification for autonomous nonlinear systems

    , 54th IEEE Conference on Decision and Control, Publisher: IEEE, Pages: 127-132

    The problem of identifying deterministic autonomous linear and nonlinear systems is studied. A specific version of the theory of deterministic subspace identification for discrete-time autonomous linear systems is developed in continuous time. By combining the subspace approach to linear identification and the differential-geometric approach to nonlinear control systems, a novel identification framework for continuous-time autonomous nonlinear systems is developed.
  • Conference paper
    Padoan A, Astolfi A, 2015,

    Dimension estimation for autonomous nonlinear systems

    , 54th IEEE Conference on Decision and Control, Publisher: IEEE, Pages: 103-108

    The problem of estimating the dimension of the state-space of an autonomous nonlinear system is considered. Assuming that sampled measurements of the output and finitely many of its time derivatives are available, an exhaustive search algorithm able to retrieve the dimension of the minimal state-space realization is proposed. The performance of the algorithm are evaluated on specific nonlinear systems.
  • Journal article
    Jiang J, Astolfi A, 2015,

    State and output-feedback shared-control for a class of linear constrained systems

    , IEEE Transactions on Automatic Control, Vol: 61, Pages: 3209-3214, ISSN: 0018-9286

    This paper presents state and output feedback sharedcontrol algorithms for a class of linear systems in the presence of constraints on the output described by means of linear inequalities. The properties of the closed-loop shared-control systems are studied using Lyapunov arguments. Simulation results demonstrate the effectiveness of the algorithm.
  • Journal article
    Yin J, Lin D, Parisini T, Ron Hui SYet al., 2015,

    Front-End Monitoring of the Mutual Inductance and Load Resistance in a Series-Series Compensated Wireless Power Transfer System

    , IEEE Transactions on Power Electronics, Vol: 31, Pages: 7339-7352, ISSN: 1941-0107

    In this paper, a new method to estimate the mutual inductance and load resistance in a series-series compensated wireless power transfer system is presented. Reasonably accurate estimations can be obtained from measurements of the input voltage and current obtained at one operating frequency only. The proposal can be used to dynamically monitor both the coupling relationship between the transmitter and receiver coils and the load conditions without any direct measurement on the receiver side. It can also be used as a simple method to measure the mutual inductance of any pair of coupled coils. A novel impedance spectrum analysis method is further presented to show that series-series compensation has special characteristics in its input impedance spectrum. Experimental results with acceptable tolerance are included to show the effectiveness of the proposed method.
  • Conference paper
    Palma V, Suardi A, Kerrigan EC, 2015,

    Sensitivity-based multistep MPC for embedded systems

    , 5th IFAC Conference on Nonlinear Model Predictive Control 2015 (NMPC'15), Publisher: Elsevier, Pages: 360-365, ISSN: 1474-6670

    In model predictive control (MPC), an optimization problem is solved every sampling instant to determine an optimal control for a physical system. We aim to accelerate this procedure for fast systems applications and address the challenge of implementing the resulting MPC scheme on an embedded system with limited computing power. We present the sensitivity-based multistep MPC, a strategy which considerably reduces the computing requirements in terms of floating point operations (FLOPs), compared to a standard MPC formulation, while fulfilling closed- loop performance expectations. We illustrate by applying the method to a DC-DC converter model and show how a designer can optimally trade off closed-loop performance considerations with computing requirements in order to fit the controller into a resource-constrained embedded system.
  • Conference paper
    Kerrigan EC, 2015,

    Feedback and time are essential for the optimal control of computing systems

    , 5th IFAC Conference on Nonlinear Model Predictive Control, Publisher: Elsevier, Pages: 380-387, ISSN: 1474-6670

    The performance, reliability, cost, size and energy usage of computing systems can be improved by one or more orders of magnitude by the systematic use of modern control and optimization methods. Computing systems rely on the use of feedback algorithms to schedule tasks, data and resources, but the models that are used to design these algorithms are validated using open-loop metrics. By using closed-loop metrics instead, such as the gap metric developed in the control community, it should be possible to develop improved scheduling algorithms and computing systems that have not been over-engineered. Furthermore, scheduling problems are most naturally formulated as constraint satisfaction or mathematical optimization problems, but these are seldom implemented using state of the art numerical methods, nor do they explicitly take into account the fact that the scheduling problem itself takes time to solve. This paper makes the case that recent results in real-time model predictive control, where optimization problems are solved in order to control a process that evolves in time, are likely to form the basis of scheduling algorithms of the future. We therefore outline some of the research problems and opportunities that could arise by explicitly considering feedback and time when designing optimal scheduling algorithms for computing systems.
  • Conference paper
    Boem F, Parisini T, 2015,

    Distributed model-based fault diagnosis with stochastic uncertainties

    , 2015 54th IEEE Conference on Decision and Control (CDC), Publisher: IEEE, Pages: 4474-4479, ISSN: 0743-1546

    This paper proposes a novel distributed fault detection and isolation approach for the monitoring of non linear large-scale systems. The proposed architecture considers stochastic characterization of the measurement noises and modeling uncertainties, computing at each step stochastic time-varying thresholds with guaranteed false alarms probability levels. The convergence properties of the distributed estimation are demonstrated. A novel fault isolation method is proposed basing on a Generalized Observer Scheme, providing guaranteed error probabilities of the fault exclusion task. A consensus approach is used for the estimation of variables shared among more than one subsystem; a method is proposed to define the time-varying consensus weights in order to minimize at each step the variance of the uncertainty of the fault detection and isolation thresholds. Detectability and isolability conditions are provided.
  • Conference paper
    Boem F, Sabattini L, Secchi C, 2015,

    Decentralized state estimation for heterogeneous multi-agent systems

    , 2015 54th IEEE Conference on Decision and Control (CDC), Publisher: IEEE, Pages: 4121-4126, ISSN: 0743-1546

    The paper proposes a decentralized state estimation method for the control of multi-agent networked systems, where the goal is the tracking of arbitrary setpoint functions. The cooperative agents are partitioned into independent robots, providing the control inputs, and dependent robots, controlled by local interaction laws. The proposed state estimation algorithm allows the independent robots to estimate the state of the dependent robots in a completely decentralized way. To do that, it is necessary for each independent robot to estimate the control input components computed by the other independent robots, without requiring communication among the independent robots. The decentralized state estimator, including an input estimator, is developed and the convergence properties are studied. Simulation results show the effectiveness of the proposed approach.
  • Conference paper
    Scarciotti G, 2015,

    Model reduction by moment matching for linear singular systems

    , 2015 54th IEEE Conference on Decision and Control (CDC), Pages: 7310-7315, ISSN: 0743-1546
  • Conference paper
    Scarciotti G, Astolfi A, 2015,

    Model reduction for nonlinear systems and nonlinear time-delay systems from input/output data

    , 2015 54th IEEE Conference on Decision and Control (CDC), Publisher: IEEE, Pages: 7298-7303, ISSN: 0743-1546
  • Journal article
    Manfredi S, Angeli D, 2015,

    Frozen state conditions for exponential consensus of time-varying cooperative nonlinear networks

    , Automatica, Vol: 64, Pages: 182-189, ISSN: 1873-2836

    In this paper we present new results on exponential consensus for continuous-time nonlinear time varying cooperative networks. We endow the well known assumption of integral connectivity proposed by Moreau with a remarkable additional feature of being frozen in state variables, making its direct verification more straightforward. Moreover, we give an estimate of the exponential rate of convergence towards the agreement space. Finally, the proposed results are validated for representative examples.
  • Journal article
    Angeli D, Efimov D, 2015,

    Characterizations of Input-to-State Stability for systems with multiple invariant sets

    , IEEE Transactions on Automatic Control, Vol: 60, Pages: 3242-3256, ISSN: 0018-9286

    We generalize the theory of Input-to-State Stability (ISS) and of its characterizations by means of Lyapunov dissipation inequalities to the study of systems admitting invariant sets, which are not necessarily stable in the sense of Lyapunov but admit a suitable hierarchical decomposition. It is the latter which allows to greatly extend the class of systems to which ISS theory can be applied, allowing in a unified treatment to deal with oscillators in Euclidean coordinates, almost globally asymptotically stable systems on manifolds, systems with multiple equilibria in Rn just to name a few.
  • Journal article
    Segundo Sevilla FR, Jaimoukha I, Chaudhuri B, Korba Pet al., 2015,

    A semidefinite relaxation procedure for fault-tolerant observer design

    , IEEE Transactions on Automatic Control, Vol: 60, Pages: 3332-3337, ISSN: 0018-9286

    A fault-tolerant observer design methodology is proposed. The aim is to guarantee a minimum level of closed-loop performance under all possible sensor fault combinations while optimizing performance under the nominal, fault-free condition. A novel approach is proposed to tackle the combinatorial nature of the problem, which is computationally intractable even for a moderate number of sensors, by recasting the problem as a robust performance problem, where the uncertainty set is composed of all combinations of a set of binary variables. A procedure based on an elimination lemma and an extension of a semidefinite relaxation procedure for binary variables is then used to derive sufficient conditions (necessary and sufficient in the case of one binary variable) for the solution of the problem which significantly reduces the number of matrix inequalities needed to solve the problem. The procedure is illustrated by considering a fault-tolerant observer switching scheme in which the observer outputs track the actual sensor fault condition. A numerical example from an electric power application is presented to illustrate the effectiveness of the design.
  • Journal article
    Chen H-T, Tan S-C, Hui SYR, 2015,

    Nonlinear Dimming and Correlated Color Temperature Control of Bicolor White LED Systems

    , IEEE TRANSACTIONS ON POWER ELECTRONICS, Vol: 30, Pages: 6934-6947, ISSN: 0885-8993
  • Conference paper
    Jiang J, Astolfi A, 2015,

    Shared-Control for a UAV Operating in the 3D Space

    , European Control Conference 2015, Publisher: IEEE

    This paper presents a shared-control scheme for a UAV moving in a 3D space while its feasible Cartesian position set is defined by a group of linear inequalities. A hysteresis switch is used to combine the human input and the feedback control input based on the definitions of a safe set, a hysteresis set and a “dangerous” set. Case studies given in the paper show the effectiveness of the shared-control algorithm.
  • Conference paper
    Suardi A, Kerrigan EC, Constantinides GA, 2015,

    Fast FPGA prototyping toolbox for embedded optimization

    , European Control Conference (ECC), Publisher: IEEE, Pages: 2589-2594

    Traditionally compute-intensive optimisation algorithms have been implemented on CPU based machines, primarily in order to reduce development time, but sacrificing computing speed and energy consumption. However, recent advancements in FPGA technologies are making the design effort comparable to that of CPUs, making them an increasingly viable option. This paper presents FPGA IP prototyping toolbox (PROTOIP), which is an Open Source framework conceived to enable researchers and engineers to design, validate and prototype algorithms quickly on FPGA platforms. Abstracting many low-level FPGA design details, PROTOIP provides custom templates, scripts, example designs and tutorials specifically tailored for embedded optimization applications.
  • Journal article
    Ionescu TC, Astolfi A, 2015,

    Nonlinear moment matching-based model order reduction

    , IEEE Transactions on Automatic Control, Vol: 61, Pages: 2837-2847, ISSN: 0018-9286

    In this paper we present a time-domain notion of moments for a class of single-input, single-output nonlinear systems in terms of the evolution of the output of a generalized signal generator driven by the nonlinear system. We also define a new notion of moment matching and present a family of (nonlinear) parametrized reduced order models that achieve moment matching. We establish relations with existing notions of moment for nonlinear systems, showing that the newly derived and the existing families of reduced order models that achieve nonlinear moment matching, respectively, are equivalent. Furthermore, we compute the reduced order model that matches the moments at two chosen signal generators (one exciting the input of the system and another driven by the system), simultaneously. We also present a family of models computed on the basis of a nonlinear extension of the Petrov-Galerkin projection that achieve moment matching. Finally, we specialize the results to the case of nonlinear, input-affine systems.
  • Journal article
    Vinter RB, 2015,

    Multifunctions of bounded variation

    , Journal of Differential Equations, Vol: 260, Pages: 3350-3379, ISSN: 1090-2732

    Consider control systems described by a differential equation with a control term or, more generally, by a differential inclusion with velocity set F(t,x). Certain properties of state trajectories can be derived when it is assumed that F(t,x) is merely measurable w.r.t. the time variable t . But sometimes a refined analysis requires the imposition of stronger hypotheses regarding the time dependence. Stronger forms of necessary conditions for minimizing state trajectories can be derived, for example, when F(t,x) is Lipschitz continuous w.r.t. time. It has recently become apparent that significant addition properties of state trajectories can still be derived, when the Lipschitz continuity hypothesis is replaced by the weaker requirement that F(t,x) has bounded variation w.r.t. time. This paper introduces a new concept of multifunctions F(t,x) that have bounded variation w.r.t. time near a given state trajectory, of special relevance to control. We provide an application to sensitivity analysis.
  • Conference paper
    Manfredi S, Angeli D, 2015,

    On exponential consensus for time-varying non-cooperative nonlinear networks

    , ECC 2015, Publisher: IEEE, Pages: 557-562

    In this paper we present new results on asymptotic consensus for continuous-time nonlinear time varying networks. A key feature in the following is that the monotonicity property (i.e. cooperativity) is not required, unlike most of existing literature on the subject. Additionally, we extend the use of a 'State Frozen' concept [16] and integral connectivity to this non-trivial scenario, and give condition for consensus with the additional merit to be frozen in state variables and therefore of simpler verification. Finally, we give an estimate of the exponential rate of convergence towards the agreement manifold.
  • Conference paper
    Scarciotti G, Astolfi A, 2015,

    Model reduction for linear systems and linear time-delay systems from input/output data

    , 2015 European Control Conference (ECC), Publisher: IEEE, Pages: 334-339

    An algorithm for the estimation of the moments of linear systems and linear time-delay systems from input/output data is proposed. The estimate, which converges to the moments of the system, is exploited to construct a family of reduced order models. These models asymptotically match the moments of the unknown system to be reduced. The computational complexity of the algorithm is analyzed and the use of the algorithm is illustrated by a benchmark example.
  • Journal article
    Ho GKY, Zhang C, Pong BMH, Hui SYRet al., 2015,

    Modeling and Analysis of the Bendable Transformer

    , IEEE Transactions on Power Electronics, Vol: 31, Pages: 6450-6460, ISSN: 0885-8993

    This paper presents a study of a bendable transformer for wearable electronics. Printed on a thin and bendable film, this transformer is bendable to wrap around body limbs such as the forearm. A model using a partial equivalent circuit theory has been developed to analyze the characteristic of an inductor and a bendable transformer. The mutual inductance and self-inductance for the bendable transformer over a range of bent curvatures have been calculated based on the model and compared favorably with measurements. Simulation and experimental results of applying the bendable inductor and transformer in dc-dc converters as a 5-V 500-mA power supply are included to confirm the usefulness of the transformer and the validity of the model.
  • Journal article
    Bachtiar V, Kerrigan EC, Moase WH, Manzie Cet al., 2015,

    Continuity and Monotonicity of the MPC Value Function with respect to Sampling Time and Prediction Horizon

    , Automatica, Vol: 63, Pages: 330-337, ISSN: 1873-2836

    The digital implementation of model predictive control (MPC) is fundamentally governed by two design parameters; samplingtime and prediction horizon. Knowledge of the properties of the value function with respect to the parameters can be used fordeveloping optimisation tools to find optimal system designs. In particular, these properties are continuity and monotonicity.This paper presents analytical results to reveal the smoothness properties of the MPC value function in open- and closed-loopfor constrained linear systems. Continuity of the value function and its differentiability for a given number of prediction stepsare proven mathematically and confirmed with numerical results. Non-monotonicity is shown from the ensuing numericalinvestigation. It is shown that increasing sampling rate and/or prediction horizon does not always lead to an improved closedloopperformance, particularly at faster sampling rates.
  • Journal article
    Zhao Z, Yang P, Cai Z, Zhou S, Green TC, Lei Jet al., 2015,

    Analysis and improvement of steady-state voltage stability for isolated medium-voltage microgrid with wind power

    , Dianli Zidonghua Shebei Electric Power Automation Equipment, Vol: 35, Pages: 13-19, ISSN: 1006-6047

    The power-voltage characteristics of DFIG (Doubly-Fed Induction Generator) with wind turbine in the isolated microgrid are analyzed and a strategy based on the local energy-storage stability control and fast pitch-angle control is proposed according to the constraints of different operating modes of microgrid with DFIG to enhance its steady-state voltage stability control. A model of microgrid system with stability control strategy is built based on PSCAD /EMTDC and the results of research indicate that, the proposed strategy enhances effectively the steady-state voltage stability of microgrid under the wind disturbances in different operating modes to guarantee its safe and stable operation.
  • Journal article
    Mayne D, Falugi P, 2015,

    Generalised stabilizing conditions for model predictive control

    , Journal of Optimization Theory and Applications, Vol: 169, Pages: 719-734, ISSN: 1573-2878

    This note addresses the tracking problem for model predictive control. It presents simple procedures for both linear and nonlinear constrained model predictive control when the desired equilibrium state is any point in a specified set. The resultant region of attraction is the union of the regions of attraction for each equilibrium state in the specified set and is therefore larger than that obtained when conventional model predictive control is employed.

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