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Jun-ichi Imura

Publications and source records attributed to Jun-ichi Imura.

18 recordsLinked to original sources

Chance-constrained probability measure optimization

Stochastic optimization with chance constraints often relies on deterministic decision-making, where optimal decisions are fixed and may be applied to a system repeatedly. A critical question arises: Can probabilistic decision-making, where probability measures/distributions are considered as decision variables, outperform deterministic decision-making in terms of the expected performance when chance constraints are present? This paper addresses this question by introducing the \textit{Chance-Constrained Probability Measure Optimization} (CCPMO) framework, which formulates the problem of optimizing probabilistic decisions under chance constraints. We first establish the existence of the optimal solution to CCPMO. Crucially, we prove that the optimal probabilistic decisions can always be represented by a probability measure concentrated on only two points, thereby reducing the CCPMO problem to an equivalent, simplified form. To solve this reduced problem, we propose a sample-based smooth approximation method. This approach leverages samples of model uncertainties to construct an approximate problem with uniform convergence and probabilistic feasibility guarantees. The approximate problem can be efficiently solved using standard nonlinear programming techniques. Finally, we validate the proposed framework through a numerical example of a quadrotor control problem under turbulent conditions. The results demonstrate that probabilistic decision-making outperforms deterministic approaches in expected performance while satisfying safety-critical chance constraints.

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Resilient Distribution Network Planning against Dynamic Malicious Power Injection Attacks

Active distribution networks facilitating bidirectional power exchange with renewable energy resources are susceptible to cyberattacks due to integration of a diverse array of cyber components. This study introduces a grid-level defense strategy aimed at enhancing attack resiliency based on distribution network planning. Our proposed framework imposes a security requirement into existing planning methodologies, ensuring that voltage deviation from its rated value remains within a tolerable range against dynamically and maliciously injected power at end-user nodes. Unfortunately, the formulated problem in its original form is intractable because it is an infinite-dimensional bi-level optimization problem over a function space. To address this complexity, we develop an equivalent transformation into a tractable form as mixed-integer linear program leveraging linear dynamical system theory and graph theory. Notably, our investigation reveals that the severity of potential attacks hinges solely on the cumulative reactances over the path from the substation to the targeted node, thereby reducing the problem to a finite-dimensional problem. Further, the bi-level optimization problem is reduced to a single-level optimization problem by using a technique utilized in solving the shortest path problem. Through extensive numerical simulations conducted on a 54-node distribution network benchmark, our proposed methodology exhibits a noteworthy 29.3% enhancement in the resiliency, with a mere 2.1% uptick in the economic cost.

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Disconnection-aware Attack Detection and Isolation with Separation-based Detector Reconfiguration

This study addresses incident handling during an adverse event for dynamical networked control systems. Incident handling can be divided into five steps: detection, analysis, containment, eradication, and recovery. For networked control systems, the containment step can be conducted through physical disconnection of an attacked subsystem. In accordance with the disconnection, the equipped attack detection unit should be reconfigured to maintain its detection capability. In particular, separating the detection subunit associated with the disconnected subsystem is considered as a specific reconfiguration scheme in this study. This paper poses the problem of disconnection-aware attack detection and isolation with the separation-based detector reconfiguration. The objective is to find an attack detection unit that preserves its detection and isolation capability even under any possible disconnection and separation. The difficulty arises from network topology variation caused by disconnection that can possibly lead to stability loss of the distributed observer inside the attack detection unit. A solution is proposed based on an existing controller design technique referred to as retrofit control. Furthermore, an application to low-voltage power distribution networks with distributed generation is exhibited. Numerical examples evidence the practical use of the proposed method through a benchmark distribution network.

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Parameterization of All Output-Rectifying Retrofit Controllers

This study investigates a parameterization of all output-rectifying retrofit controllers for distributed design of a structured controller. It has been discovered that all retrofit controllers can be characterized as a constrained Youla parameterization, which is difficult to solve analytically. For synthesis, a tractable and insightful class of retrofit controllers, referred to as output-rectifying retrofit controllers, has been introduced. An unconstrained parameterization of all output-rectifying retrofit controllers can be derived under a technical assumption on measurability of particular signals. The aim of this note is to reveal the structure of all output-rectifying retrofit controllers in the general output-feedback case. It is found out that the existing developments can be generalized based on the notions of state projection and an inverse system. The result leads to the conclusion that output-rectifying retrofit controllers can readily be designed even in the general case.

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Distributed Design of Glocal Controllers via Hierarchical Model Decomposition

This paper proposes a distributed design method of controllers having a glocal (global/local) information structure for large-scale network systems. Distributed design, independent design of all subcontrollers that constitute a structured controller, facilitates scalable controller synthesis. While existing distributed design methods confine attention to the decentralized or distributed information structures, this study addresses distributed design of glocal-structured controllers. Glocal control exploits the nature that network system's behavior can typically be represented as a superposition of spatially local fluctuations and global interarea oscillations by incorporating a global coordinating subcontroller with local decentralized subcontrollers. The key idea to distributed design of glocal controllers is to represent the original network system as a hierarchical cascaded system composed of reduced-order models representing the global and local dynamics, referred to as hierarchical model decomposition. Distributed design is achieved by independently designing and implementing subcontrollers for the reduced-order models while preserving the cascade structure. This paper provides a condition for existence of the hierarchical model decomposition, a specific representation of the hierarchical system, a clustering method appropriate for the proposed approach, and a robust extension. Numerical examples of a power grid evidence the practical relevance of the proposed method.

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Fast Online Reinforcement Learning Control using State-Space Dimensionality Reduction

In this paper, we propose a fast reinforcement learning (RL) control algorithm that enables online control of large-scale networked dynamic systems. RL is an effective way of designing model-free linear quadratic regulator (LQR) controllers for linear time-invariant (LTI) networks with unknown state-space models. However, when the network size is large, conventional RL can result in unacceptably long learning times. The proposed approach is to construct a compressed state vector by projecting the measured state through a projective matrix. This matrix is constructed from online measurements of the states in a way that it captures the dominant controllable subspace of the open-loop network model. Next, a RL-controller is learned using the reduced-dimensional state instead of the original state such that the resultant cost is close to the optimal LQR cost. Numerical benefits as well as the cyber-physical implementation benefits of the approach are verified using illustrative examples including an example of wide-area control of the IEEE 68-bus benchmark power system.

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Modularity-in-Design of Dynamical Network Systems: Retrofit Control Approach

In this paper, we develop a modular design method of decentralized controllers for linear dynamical network systems, where multiple subcontroller designers aim at individually regulating their local control performance with accessibility only to their respective subsystem models. First, we derive a constrained version of the Youla parameterization that characterizes all retrofit controllers for a single subcontroller, defined as an add-on type subcontroller that manages a subsystem. The resultant feedback system is kept robustly stable for any variation in the neighboring subsystems, other than the subsystem of interest, provided that the original system is stable prior to implementing the retrofit control. Subsequently, we find out a unique internal structure of the retrofit controllers, assuming that the interaction input signal from the neighboring subsystems is measurable. Furthermore, we show that the simultaneous implementation of multiple retrofit controllers, designed by individual subcontroller designers, can improve the upper bound of the overall control performance. Finally, the practical significance of the method is demonstrated via an illustrative example of frequency regulation using the IEEE 68-bus power system model.

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Parameterization of Retrofit Controllers

This study investigates a parameterization of all retrofit controllers. Retrofit control can accomplish modular design of control systems, i.e., independent design of subcontrollers only with its corresponding subsystem model in a dynamical network system. In the retrofit control framework, the network system to be controlled is regarded as an interconnected system composed of the subsystem of interest and an environment. Existing studies have revealed that all retrofit controllers can be characterized as a constrained Youla parameterization under the technical assumption that the subsystem of interest is stable. It has also been discovered that all of the retrofit controllers that belong to a particular tractable class have a distinctive internal structure composed of a rectifier and an internal controller under the additional technical assumption that the interconnection signal from the environment to the subsystem of interest is measurable or that the internal state of the subsystem of interest is measurable. Due to the internal structure, the retrofit controller design problem under the assumptions can be reduced to a standard controller design problem to which existing controller synthesis techniques can be applied. The aim of this paper is to extend the above results without the technical assumptions. It is found that the existing developments can naturally be generalized through the Youla parameterization for unstable systems and an explicit description of the inverse system with the geometric control theory. The result leads to the conclusion that retrofit controllers can readily be designed even in the general case.

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Disconnection-aware Attack Detection in Networked Control Systems

This study deals with security issues in dynamical networked control systems. The goal is to establish a unified framework of the attack detection stage, which includes the four processes of monitoring the system state, making a decision based on the monitored signal, disconnecting the corrupted subsystem, and operating the remaining system during restoration. This paper, in particular, considers a disconnection-aware attack detector design problem. Traditionally, observer-based attack detectors are designed based on the system model with a fixed network topology and cannot cope with a change of the topology caused by disconnection. The disconnection-aware design problem is mathematically formulated and a solution is proposed in this paper. A numerical example demonstrates the effectiveness of the proposed detector through an inverter-based voltage control system in a benchmark model.

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Day-Ahead Energy Market as Adjustable Robust Optimization: Spatio-Temporal Pricing of Dispatchable Generators, Storage Batteries, and Uncertain Renewable Resources

We present modeling and analysis of day-ahead spatio-temporal energy markets in which each competitive aggregator aims at making the highest profit by managing a complex mixture of different energy resources, such as conventional generators, storage batteries, and uncertain renewable resources. First, we develop an energy market model in terms of an adjustable robust convex program. This market modeling is novel in the sense that the prosumption cost function of each aggregator, which evaluates the cost to realize an amount of spatio-temporal energy prosumption, is a multi-variable function resulting from a "parameterized" max-min program, in which the variable of the prosumption cost function is involved as a continuous parameter and the variable of dispatchable resources is involved as an adjustable variable for energy balance. This formulation enables to reasonably evaluate a reward for intertemporal dispatchability enhancement and a penalty for renewable energy uncertainty in a unified way. In addition, it enables to enforce a market regulation in which every aggregator is responsible for absorbing his renewable energy uncertainty by managing his own dispatchable energy resources. Second, in view of social economy as well as personal economy, we conduct a numerical analysis on the premise of several photovoltaic penetration levels. In this numerical analysis, we demonstrate that renewable generators do not always have priority of energy supply higher than conventional generators due to their uncertainty and limited dispatchability, meaning that the merit order of conventional and renewable generators can reverse. Furthermore, we analyze long-term evolution of competitive energy markets demonstrating that there can be found a social equilibrium of battery penetration levels, at which maximum personal profit with respect to battery system enhancement is attained.

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Retrofit Control with Approximate Environment Modeling

In this paper, we develop a retrofit control method with approximate environment modeling. Retrofit control is a modular control approach for a general stable network system whose subsystems are supposed to be managed by their corresponding subsystem operators. From the standpoint of a single subsystem operator who performs the design of a retrofit controller, the subsystems managed by all other operators can be regarded as an environment, the complete system model of which is assumed not to be available. The proposed retrofit control with approximate environment modeling has an advantage that the stability of the resultant control system is robustly assured regardless of not only the stability of approximate environment models, but also the magnitude of modeling errors, provided that the network system before implementing retrofit control is originally stable. This robustness property is practically significant to incorporate existing identification methods of unknown environments, because the accuracy of identified models may neither be reliable nor assurable in reality. Furthermore, we conduct a control performance analysis to show that the resultant performance can be regulated by adjusting the accuracy of approximate environment modeling. The efficiency of the proposed retrofit control is shown by numerical experiments on a network of second-order oscillators.

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Dynamic Modeling, Stability, and Control of Power Systems with Distributed Energy Resources

This article presents a suite of new control designs for next-generation electric smart grids. The future grid will consist of thousands of non-conventional renewable generation sources such as wind, solar, and energy storage. These new components are collectively referred to as distributed energy resources (DER). The article presents a comprehensive list of dynamic models for DERs, and shows their coupling with the conventional generators and loads. It then presents several innovative control designs that can be used for facilitating large-scale DER integration. Ideas from decentralized retrofit control and distributed sparsity-promoting optimal control are used for developing these designs, followed by illustrations on an IEEE power system test model.

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Retrofit Control: Localization of Controller Design and Implementation

In this paper, we propose a retrofit control method for stable network systems. The proposed approach is a control method that, rather than an entire system model, requires a model of the subsystem of interest for controller design. To design the retrofit controller, we use a novel approach based on hierarchical state-space expansion that generates a higher-dimensional cascade realization of a given network system. The upstream dynamics of the cascade realization corresponds to an isolated model of the subsystem of interest, which is stabilized by a local controller. The downstream dynamics can be seen as a dynamical model representing the propagation of interference signals among subsystems, the stability of which is equivalent to that of the original system. This cascade structure enables a systematic analysis of both the stability and control performance of the resultant closed-loop system. The resultant retrofit controller is formed as a cascade interconnection of the local controller and an output rectifier that rectifies an output signal of the subsystem of interest so as to conform to an output signal of the isolated subsystem model while acquiring complementary signals neglected in the local controller design, such as interconnection signals from neighboring subsystems. Finally, the efficiency of the retrofit control method is demonstrated through numerical examples of power systems control and vehicle platoon control.

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Synchronization and Aggregation of Nonlinear Power Systems with Consideration of Bus Network Structures

We study nonlinear power systems consisting of generators, generator buses, and non-generator buses. First, looking at a generator and its bus' variables jointly, we introduce a synchronization concept for a pair of such joint generators and buses. We show that this concept is related to graph symmetry. Next, we extend, in two ways, the synchronization from a pair to a partition of all generators in the networks and show that they are related to either graph symmetry or equitable partitions. Finally, we show how an exact reduced model can be obtained by aggregating the generators and associated buses in the network when the original system is synchronized with respect to a partition, provided that the initial condition respects the partition. Additionally, the aggregation-based reduced model is again a power system.

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Transient Response Improvement for Interconnected Linear Systems: Low-Dimensional Controller Retrofit Approach

In this paper, we propose a method of designing low-dimensional retrofit controllers for interconnected linear systems. In the proposed method, by retrofitting an additional low-dimensional controller to a preexisting control system, we aim at improving transient responses caused by spatially local state deflections, which can be regarded as a local fault occurring at a specific subsystem. It is found that a type of state-space expansion, called hierarchical state-space expansion, is the key to systematically designing a low-dimensional retrofit controller, whose action is specialized to controlling the corresponding subsystem. Furthermore, the state-space expansion enables theoretical clarification of the fact that the performance index of the transient response control is improved by appropriately tuning the retrofit controller. The efficiency of the proposed method is shown through a motivating example of power system control where we clarify the trade-off relation between the dimension of a retrofit controller and its control performance.

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A Retrofitting-based Supplementary Controller Design for Enhancing Damping Performance of Wind Power Systems

In this paper we address the growing concerns of wind power integration from the perspective of power system dynamics and stability. We propose a new retrofit control technique where an additional controller is designed at the doubly-fed induction generator site inside the wind power plant. This controller cancels the adverse impacts of the power flow from the wind side to the grid side on the dynamics of the overall power system. The main advantage of this controller is that it can be implemented by feeding back only the wind states and wind bus voltage without depending on any of the other synchronous machines in the rest of the system. Through simulations of a 4-machine Kundur power system model we show that the retrofit can efficiently enhance the damping performance of the system variable despite very high values of wind penetration.

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Weak Resilience of Networked Control Systems

In this paper, we propose a method to establish a networked control system that maintains its stability in the presence of certain undesirable incidents on local controllers. We call such networked control systems weakly resilient. We first derive a necessary and sufficient condition for the weak resilience of networked systems. Networked systems do not generally satisfy this condition. Therefore, we provide a method for designing a compensator which ensures the weak resilience of the compensated system. Finally, we illustrate the efficiency of the proposed method by a power system example based on the IEEE 14-bus test system.

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Effects of time delay in feedback control of linear quantum systems

We investigate feedback control of linear quantum systems subject to feedback-loop time delays. In particular, we examine the relation between the potentially achievable control performance and the time delays, and provide theoretical guidelines for the future experimental setup in two physical systems, which are typical in this research field. The evaluation criterion for the analysis is given by the optimal control performance formula, the derivation of which is from the classical control theoretic results about the input-output delay systems.

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