Dehui Sun

Data-Based Predictive Control for Networked Nonlinear Systems With Network-Induced Delay and Packet Dropout

This paper addresses the data-based networked control problem for a class of nonlinear systems. Network communication constraints, such as network-induced delay, packet disorder, and packet dropout in both the feedback and forward channels, are considered and further treated as the round-trip time (RTT) delay that is redefined. By using the packet-based transmission mechanism and the model-free adaptive control algorithm, a data-based networked predictive control method is proposed to actively compensate for the random RTT delay. The proposed method does not require any information on the plant model and depends only on the input and output data of the plant. A simple and explicit sufficient condition, which is related to the upper bound of the RTT delays, is derived for the stability of the closed-loop system. Additionally, a zero steady-state output tracking error can be achieved for a step reference input. The effectiveness of the proposed method is demonstrated via simulation and experimental results.

Two-Channel False Data Injection Attacks Against Output Tracking Control of Networked Systems

This paper addresses the design problem of false data injection (FDI) attacks against the output tracking control of networked systems, where the network-induced delays in the feedback and forward channels are considered. The main contributions of this paper are as follows. 1) To actively compensate for the two-channel network-induced delays, a Kalman filter-based networked predictive control scheme is designed for stochastic linear discrete-time systems. 2) From an attackers perspective, stealthy FDI attacks are proposed for both the feedback and forward channels so as to disrupt the stability of the resulting closed-loop system while avoiding the detection of a Kalman filter-based attack detector. 3) Both numerical simulations and practical experiments are carried out to show the effectiveness of the proposed method.

Data-Driven Control With Input Design-Based Data Dropout Compensation for Networked Nonlinear Systems

This brief investigates the regulation problem for a class of networked nonlinear systems with measurement noise, where random data dropouts in both the feedback and forward channels are considered. To actively compensate for the two-channel data dropouts, a data-driven networked compensation control method is proposed, which consists of two aspects: 1) to calculate a control increment based on the measured output error in the controller and 2) to design a data dropout compensation strategy based on the latest control increment available in the actuator. The proposed method merely depends on the input and output data of the controlled plant, without using explicit or implicit information of its mathematical model. Moreover, only one control command needs to be transmitted in the forward channel at each time instant. A sufficient condition is derived to guarantee the closed-loop stability and output error convergence. Both numerical simulations and experimental tests are conducted to demonstrate the effectiveness of the proposed method.

False data injection attacks for a class of output tracking control systems

With the development of cyber-physical systems (CPSs), the security becomes an important and challenging problem. Attackers can launch various attacks to destroy the control system performance. In this paper, a class of linear discrete-time time-invariant control systems is considered, which is open-loop critically stable and only has one critical eigenvalue. By including the output tracking error as an additional state, a Kalman filter-based augmented state feedback control strategy is designed to solve its output tracking problem. Then a stealthy false data attack is injected into the measurement output, which can completely destroy the output tracking control systems without being detected. Simulation results on a numerical example show that the proposed false data injection attack is effective.

State feedback stabilization of single-input min-max-plus systems

Min-max-plus systems are discrete-event systems in which the operations minimum, maximum and addition appear simultaneously. This paper describes a general model of single-input min-max-plus systems and proposes the concept of the state feedback stabilization for these systems. It is derived that the reachable single-input min-max-plus systems can be stabilized using the max-plus linear state feedback. The method based on max-plus algebra is constructive in nature and yields a direct design to achieve the feedback stabilization.

Networked Predictive Control Based on State-Space Model

This chapter is devoted to the networked control of multiple-input multiple-output linear systems, where random network-induced delays, packet disorders, and packet dropouts in the feedback and forward channels are considered. To compensate for these communication constraints, a networked predictive control method is presented based on a state-space model. A stability condition is derived for the resulting closed-loop networked system, which also shows that the separation principle of the observer-based controller design still holds. Simulation and experimental results are given to illustrate the effectiveness of the proposed method.

Secure Networked Predictive Control Under DoS Attacks

This chapter is concerned with DoS attacks in NCSs, which are classified as weak attacks and strong attacks. For an NCS under weak DoS attacks, a networked predictive control method is designed to actively compensate for original RTT delays induced by communication networks and additional RTT delays introduced by weak DoS attacks. For an NCS under strong DoS attacks against networked controllers or communication channels, a multi-controller switching strategy is presented based on a networked predictive control scheme, which can guarantee the closed-loop control performance even if the current controller fails to work or the communication between the controller and the plant is cut off. Practical experiments are conducted to illustrate the effectiveness of the proposed methods.

A Data Secure Transmission Scheme for Deception Attacks

This chapter focuses on the security of the data transmitted over networks, and a data secure transmission scheme is designed where confidentiality, integrity, and authenticity are addressed. To ensure the confidentiality, the Data Encryption Standard (DES) cipher is used to encrypt the data transmitted over networks. The violation of integrity and authenticity is known as deception attacks. The Message Digest 5 (MD5) algorithm and a timestamp comparison strategy are employed under the DES cryptosystem to actively detect deception attacks. Numerical simulations are provided to verify the proposed scheme.

False Data Injection Attacks Against Networked Predictive Output Tracking Control Systems

This chapter discusses the design problem of stealthy FDI attacks against NCSs from the viewpoint of malicious attackers. A Kalman filter-based networked predictive output tracking control method is proposed for networked MIMO stochastic linear systems, where random network-induced delays, packet disorders, and packet dropouts in the feedback and forward channels are considered. To destroy the stability of the resulting closed-loop networked system without being detected by a detector based on an output residual, stealthy FDI attacks are designed against the measurement data in the feedback channel and the control commands in the forward channel, respectively, and the corresponding attack conditions are derived. Both simulation and experimental results are given to show the effectiveness of the proposed methods.

Networked Predictive Control of Systems with Communication Constraints and Cyber Attacks

Introduction -- Part I: Networked Predictive Control of Systems with Communication Constraints -- Preliminaries for NCSs -- Networked Predictive Control Based on Linear Input-Output Models -- Incremental Networked Predictive Control Based on Linear Input-Output Models -- Networked Predictive Control Based on Nonlinear Input-Output Models -- Networked Predictive Control Based on State-Space Models -- Networked Predictive Output Tracking Control Based on State-Space Models -- Part II: Networked Predictive Control of Systems with Cyber Attacks and Communication Constraints -- Preliminaries for Cyber Attacks -- Data Secure Transmission Scheme for Deception Attacks -- Secure Networked Predictive Control under Deception Attacks and Communication Constraints -- False Data Injection Attacks against Output Tracking Control Systems -- False Data Injection Attacks against Networked Predictive Output Tracking Control System s -- Secure Networked Predictive Control under DoS Attacks and Communication Constraints.