Distributed averaging-based integral (DAI) controllers are becoming increasingly popular in power system applications. The literature has thus far primarily focused on disturbance rejection, steady-state optimality and adaption to complex physical system models without considering uncertainties on the cyber and communication layer nor their effect on robustness and performance. In this paper, we derive sufficient delay-dependent conditions for robust stability of a secondary-frequency-DAI-controlled power system with respect to heterogeneous communication delays, link failures and packet losses. Our analysis takes into account both constant as well as fast-varying delays, and it is based on a common strictly decreasing Lyapunov-Krasovskii functional. The conditions illustrate an inherent trade-off between robustness and performance of DAI controllers. The effectiveness and tightness of our stability certificates are illustrated via a numerical example based on Kundur's four-machine-two-area test system.

Robustness of Distributed Averaging Control in Power Systems: Time Delays & Dynamic Communication Topology

Multi-agent systems (MASs) has developed into an emerging complex system science and gradually infiltrated into various fields of social life. The problem of consensus (i.e. all agents eventually t...

https://www.tandfonline.com/doi/pdf/10.1080/21642583.2019.1695689

A survey of the consensus for multi-agent systems

An event-triggered distributed state estimation problem is investigated for a class of discrete-time nonlinear stochastic systems with unknown parameters over sensor networks (SNs) subject to switched topologies. An event-triggered communication strategy is employed to govern the information broadcast and reduce the unnecessary resource consumption. Based on the adopted communication strategy, a distributed state estimator is designed to estimate the plant states and also identify the unknown parameters. In the framework of input-to-state stability, sufficient conditions with an average dwell time are established to ensure the boundedness of estimation errors in mean-square sense. In addition, the gains of the designed estimators are dependent on the solution of a set of matrix inequalities whose dimensions are unrelated to the scale of underlying SNs, thereby fulfill the scalability requirement. Finally, an illustrative simulation is utilized to verify the feasibility of the proposed design scheme.

A Scalable Algorithm for Event-Triggered State Estimation With Unknown Parameters and Switching Topologies Over Sensor Networks

In this paper, the high-dimensional distributed state estimation problem is investigated for a class of sensor networks within the cubature Kalman filtering (CKF) framework. The network consists of two types of nodes, i.e., communication ones and sensor ones. First, a hybrid consensus-based cubature Kalman filtering (HCCKF) is developed by blending the two existing approaches, namely, consensus on measurements (CM) and consensus on information (CI). As a result, the proposed filtering algorithm has complementary features of CM and CI, which turns out to be a better solution to the distributed state estimation problem. Secondly, estimation errors in HCCKF are proved to be exponentially bounded in mean square. Finally, a target tracking case-study in an example sensor network is given to demonstrate the effectiveness of the proposed HCCKF.

Hybrid Consensus-Based Cubature Kalman Filtering for Distributed State Estimation in Sensor Networks

In this work, we propose a robust stabilizer for nonholonomic systems with time varying time delays and nonlinear disturbances. The proposed approach implements a composite nonlinear feedback structure in which a linear controller is designed to yield a fast response and a nonlinear feedback control law is considered to increase the system’s damping ratio. This structure results in the simultaneous improvement of the steady-state accuracy and transient performance of time-delay nonholonomic systems. Asymptotic stability of the proposed feedback control approach is derived using a Lyapunov–Krasovskii functional aimed at reaching a compromise between system’s transient performance and asymptotic stability. Simulation and analytical results are considered to highlight the robustness and superior performance of the proposed approach in controlling high-order-time-delay nonholonomic systems with nonlinear disturbances.

A composite feedback approach to stabilize nonholonomic systems with time varying time delays and nonlinear disturbances

A Lyapunov-based distributed consensus filter for a class of nonlinear stochastic systems

Unmanned systems like autonomous surface vessels are being enhanced with the communication infrastructure to improve their reliability, efficiency and sustainability. Regardless of the significance advantages, their open communication network and connectivity renders these systems to a variety of cyber-attacks. This paper considers the resilient consensus problem of multi-agent systems (MASs) under an integrity attack. Unlike the existing works in the time domain, a resilient consensus controller is designed and analyzed for MASs in the frequency domain. To this end, analysis and modeling of MASs under the integrity attacks (MU-IA) are addressed in the frequency domain in which each agent is a linear continuous system with an input time delay. A resilient H∞ controller is proposed to tackle the tampering of information due to an integrity attack. The proposed H∞ controller is designed based on an internal stability method for performance tracking and robustness of the MU-IA. A significant strength of this scheme is that the current approach does not enforce any limit on the number of agents or neighboring agents under the integrity attacks. A quantitative tuning method is used to trade off the nominal performance and robustness of the MU-IA. Simulation results show the effectiveness of the proposed control strategy.

Frequency domain analysis of resilient consensus in multi-agent systems subject to an integrity attack.

This paper establishes some distributed algorithms for nonlinear multi-agent systems to solve tracking control (TC) problem subject to external disturbances or delay. First, a distributed controller is introduced based on a distributed observer for the nodes to estimate and follow a nonlinear target. Then, utilizing a future predictor (FP) and an external disturbance observer, the proposed controller is developed for each agent with delay or disturbances to deal with TC problem. Stability of the control laws and FP is also analyzed and sufficient conditions are proposed for the TC of the multi-agent systems (MASs). Simulation examples validate the efficiency of the presented methods.

Distributed estimation and control for nonlinear multi-agent systems in the presence of input delay or external disturbances.

This paper investigates the state estimation problem for continuous-time nonlinear stochastic systems in sensor networks. For this purpose, a distributed consensus filter (DCF) is proposed based on Lyapunov stability theory for every node in a sensor network. It will be proved that the mean square of the estimation error is exponentially ultimately bounded. This filter can estimate the states of nonlinear stochastic systems, the nonlinear functions of which satisfy a pseudo Lipschitz condition. Sufficient conditions for the existence of this filter are sensor network connectivity and LMI solvability of DCF. Furthermore, a criterion is presented to optimize the filter gain based on minimizing the upper consensus bound of estimation error. Simulation results show the promising performance of the proposed filter.

https://onlinelibrary.wiley.com/doi/pdf/10.1002/asjc.1551

Distributed Consensus Filter for a Class of Continuous-Time Nonlinear Stochastic Systems in Sensor Networks

This paper investigates the tracking control problem of chained-form nonholonomic multiagent systems (MASs). In contrast to the existing works in which some algorithms have been designed for ideal conditions, the destructive factors including external disturbances and input delay are considered in the dynamics of the agents in this work. Two distributed controllers are proposed such that the states of the controlled agents can track the states of the target in the presence of external disturbances and input delay. For this purpose, a distributed controller is firstly suggested based on a switching method to solve the tracking control problem for nonholonomic MASs with external disturbances. Then, the proposed control law is extended based on a state predictor for the tracking control of agents in the presence of input delay. The stability analysis of the two distributed controllers is also provided. Simulation results show the promising performance of the proposed algorithms.

Ahmadreza Jenabzadeh

Papers

A Lyapunov-based distributed consensus filter for a class of nonlinear stochastic systems

Frequency domain analysis of resilient consensus in multi-agent systems subject to an integrity attack.

Distributed estimation and control for nonlinear multi-agent systems in the presence of input delay or external disturbances.

Distributed Consensus Filter for a Class of Continuous-Time Nonlinear Stochastic Systems in Sensor Networks

Tracking control of nonholonomic mobile agents with external disturbances and input delay.