Ahmad F. Taha

Risk Mitigation for Dynamic State Estimation Against Cyber Attacks and Unknown Inputs

Phasor measurement units (PMUs) can be effectively utilized for the monitoring and control of the power grid. As the cyber-world becomes increasingly embedded into power grids, the risks of this inevitable evolution become serious. In this paper, we present a risk mitigation strategy, based on dynamic state estimation, to eliminate threat levels from the grid’s unknown inputs and potential cyber-attacks. The strategy requires: 1) the potentially incomplete knowledge of power system models and parameters and 2) real-time PMU measurements. First, we utilize a dynamic state estimator for higher order depictions of power system dynamics for simultaneous state and unknown inputs estimation. Second, estimates of cyber-attacks are obtained through an attack detection algorithm. Third, the estimation and detection components are seamlessly utilized in an optimization framework to determine the most impacted PMU measurements. Finally, a risk mitigation strategy is proposed to guarantee the elimination of threats from attacks, ensuring the observability of the power system through available, safe measurements. Case studies are included to validate the proposed approach. Insightful suggestions, extensions, and open problems are also posed.

Decentralized Control Framework and Stability Analysis for Networked Control Systems

The combination of decentralized control and networked control where control loops are closed through a network is called decentralized networked control system (DNCS). This paper introduces a general framework that converts a generic decentralized control configuration of non-networked systems to the general setup of networked control systems (NCS). Two design methods from the literature of decentralized control for nonnetworked systems were chosen as a base for the design of a controller for the networked systems, the first being an observer-based decentralized control, while the second is the well-known Luenberger combined observer‐controller. The main idea of our design is to formulate the DNCS in the general form and then map the resulting system to the general form of the NCS. First, a method for designing decentralized observer-based controller is discussed. Second, an implementation using a network is analyzed for the two designs. Third, two methods to analyze the stability of the DNCS are also introduced. Fourth, perturbation bounds for stability of the DNCS have been derived. Finally, examples and simulation results are shown and discussed. [DOI: 10.1115/1.4028789]

Unknown input observer design and analysis for networked control systems

The insertion of communication networks in the feedback loops of control systems is a defining feature of modern control systems. These systems are often subject to unknown inputs in a form of disturbances, perturbations, or attacks. The objective of this paper is to design and analyse an observer for networked dynamical systems with unknown inputs. The network effect can be viewed as either a perturbation or time-delay to the exchanged signals. In this paper, we (1) review an unknown input observer (UIO) design for a non-networked system, (2) derive the networked unknown input observer (NetUIO) dynamics, (3) design a NetUIO such that the effect of higher delay order terms are nullified and (4) establish stability-guaranteeing bounds on the networked-induced time-delay and perturbation. The formulation and results derived in this paper can be generalised to scenarios and applications where the signals are perturbed due to a different source of perturbation or delay.

An Optimal General Purpose Scheduler for Networked Control Systems

The network-induced time delay is one of the major challenges that appear when the design or the analysis of any Networked Control System (NCS) is needed. The delay can be tackled in the network level by performing control of network actions. Since the process of prioritizing the network access is the main contributor of the network-induced time delay, then the efficient way to control the time delay is to improve the scheduling criterion. This paper proposes an optimal scheduling criterion that improves the quality of service for each node in the network and at the same time maintains the stability of the control system. The proposed optimal scheduling protocol is a hybrid scheduling criterion that combines the advantages of the dynamic and the static scheduling protocols. First, the algorithm of the optimal scheduling is discussed. Second, the optimal control-scheduling problem is formulated. The mixed logical-dynamical optimization problem is then solved. Finally, numerical examples and simulation results are introduced and discussed.

Observer-based decentralized control scheme for stability analysis of networked systems

The combination of decentralized and networked control where control loops are closed through a network is defined as Decentralized Networked Control System (DNCS). In this paper, we introduce a general framework that converts a generic decentralized control configuration of non-networked systems to the general setup of Networked Control Systems (NCS). An observer-based decentralized control method is used to illustrate the applicability of the proposed framework. First, a method for designing decentralized observer-based controllers for non-networked systems is discussed. Second, we introduce the general framework that maps the non-networked decentralized control scheme to the networked one. Third, we provide two methods to analyze the closed-loop system stability, given the proposed model. Stability perturbation bounds of the DNCS are derived. Finally, example and simulation results are shown and discussed.

A hybrid scheduling protocol to improve quality of service in networked control systems

In many networked control systems (NCSs) only one node is allowed to use the shared medium at any given time. This network constraint can adversely affect the performance of the system and its stability. There are two types of network schedulers, static and dynamic. Static schedulers, such as the token ring protocol, have problems handling large-scale systems. On the other hand, dynamic schedulers, such as try-once-discard (TOD) cannot guarantee good quality of service for each node, especially the low-priority ones. In this paper, a hybrid scheduler, which is a combination of dynamic and static protocols, is proposed. This scheduler improves the medium access strategy in large-scale control systems. We refer to this scheduler as the traffic-division arbitration (TDA) protocol. The network-induced delay error bound and the system stability of the NCS using the proposed scheduler are investigated. Simulations illustrate the performance of the proposed scheduler and difference from TOD are shown. We use two different decision functions to prioritize the scheduling criteria of the protocol.

Actuator selection for cyber-physical systems

In cyber-physical systems (CPS), the problem of controlling resources can be depicted as an actuator selection problem. Given a large library of actuators and a control objective, what is the least number of actuators to be selected, and what is the corresponding optimal control law? These dynamic design questions are inherently coupled. In this paper, we show that a breadth of actuator selection and optimal control problems (stabilizability, robust and LQR control routines, control of uncertain, nonlinear systems) that do not satisfy the submodularity property lead to the formulation of two classes of combinatorial optimization routines for unstable CPSs: mixed-integer semidefinite programs and mixed-integer bilinear matrix inequalities. Branch-and-bound and greedy algorithms are proposed to address the computational complexity, and numerical results are given to illustrate the proposed formulations.

Buildings-to-Grid Integration Framework

This paper puts forth a mathematical framework for Buildings-to-Grid (BtG) integration in smart cities. The framework explicitly couples power grid and building’s control actions and operational decisions, and can be utilized by buildings and power grids operators to simultaneously optimize their performance. Simplified dynamics of building clusters and building-integrated power networks with algebraic equations are presented---both operating at different time-scales. A model predictive control (MPC)-based algorithm that formulates the BtG integration and accounts for the time-scale discrepancy is developed. The formulation captures dynamic and algebraic power flow constraints of power networks and is shown to be numerically advantageous. The paper analytically establishes that the BtG integration yields a reduced total system cost in comparison with decoupled designs where grid and building operators determine their controls separately. The developed framework is tested on standard power networks that include thousands of buildings modeled using industrial data. Case studies demonstrate building energy savings and significant frequency regulation, while these findings carry over in network simulations with nonlinear power flows and mismatch in building model parameters. Finally, simulations indicate that the performance does not significantly worsen when there is uncertainty in the forecasted weather and base load conditions.

Assessing power system state estimation accuracy with GPS-spoofed PMU Measurements

Power grids have evolved into cyber-networks equipped with high speed communications and advanced sensors. While this evolution has been monumental, the risk of cyber-attacks is growing. In grids, phasor measurement units (PMU)-equipped with GPS receivers-are now ubiquitously installed in widespread locations, while providing real time grid-visibility. Cooperatively, limited number of PMUs can enable state estimation (SE) routines. However, PMU measurements can be notably altered via a GPS spoofing attack and consequently causing a misleading depiction of the physical status of the system. Here, we evaluate the impact of a GPS time-synchronization attack on the grids SE routines. Statistical information regarding the attacked estimates are derived with relevance to the actual state of the system. We also investigate bounds on the estimation bias introduced by the aforementioned attacks. Numerical examples are included to support the developed methods.

Augmenting the optimal power flow for stability

This paper presents an augmented optimal power flow (OPF) formulation that minimizes a power networks transient control costs using a linear quadratic regulator (LQR). The network is described by AC power flows with third-order generator dynamics modeling. Then, linearized dynamics around a known solution of the power flow equations are considered. Leveraging the equivalent linear matrix inequality formulation for the LQR, the augmented OPF (LQR-OPF) amounts to a semidefinite program, yielding optimal network steady state and an explicit feedback gain for minimum transient control cost. Numerical tests on a standard power network demonstrate the advantage of LQR-OPF in comparison to a scheme where OPF and transient control are solved separately.