This paper addresses the finite-time event-triggered control problem for nonlinear semi-Markovian switching cyber-physical systems (S-MSCPSs) under false data injection (FDI) attacks. Compared with the traditional time-triggered mechanism, the proposed event-triggered scheme (ETS) can effectively avoid network resource waste. Considering the network-induced delay in the modeling, a closed-loop system model with time delay is established in the unified framework. By the use of a mode-dependent piecewise Lyapunov-Krasovskii functional (LKF), stochastic finite-time stability (SFTS) criteria are established for the resultant closed-loop system. Then, some solvability conditions are established for the desired finite-time controller in light of a linear matrix inequality framework. Finally, an application example of vertical take-off and landing helicopter model (VTOLHM) is provided to demonstrate the effectiveness of the theoretical findings.

Finite-Time Event-Triggered Control for Semi-Markovian Switching Cyber-Physical Systems With FDI Attacks and Applications

This paper investigates the formation control problem for a group of nonholonomic mobile robots (NMRs) with unknown parameters and deception attacks. The information transmitted among different robots is represented by a directed graph and only a subset of the robots can obtain the full information of the desired trajectory directly. For those robots which cannot access to the reference trajectory directly, distributed estimators are designed to estimate the unknown trajectory information by using only locally available information. Besides, the sensor-to-controller transmitting channels and the communication among connected robots are suffering from deception attacks. Adaptive laws and compensation terms are designed to handle the issue of attack-induced uncertainties. Then, a novel distributed resilient formation control scheme is designed, based on which a sufficient condition is developed to guarantee that the formation errors converge to a compact set and all the closed-loop signals are bounded. Experimental results are given to validate the theoretical studies.

Distributed Adaptive Resilient Formation Control of Uncertain Nonholonomic Mobile Robots Under Deception Attacks

This article presents a novel dynamic event-triggered scheme for the load frequency regulation with periodic denial-of-service (DoS) attacks and deception attacks via decentralized output-based control algorithm. Compared with the existing event-triggered strategy, the proposed one automatically changes the parameters of the triggered condition by detecting the frequency trend of the DoS attack to change the release frequency, which can ensure the stability of the power system while increasing the probability of effective transmission subject to DoS attack and thus, reducing network bandwidth usage. First, the proposed dynamic event-triggered strategy combined with the decentralized output-based controller is presented in a unified framework to deal with deception attacks and DoS attacks in the multiarea power system. Then, we utilize the Lyapunov stability theory to analyze the exponential stability in the mean-square sense and the robustness of the power system. By solving a set of linear matrix inequalities (LMIs), a procedure is given for the design of output-based load frequency controllers. Finally, a three-area power system is exploited as a simulation to verify the effectiveness of the proposed results.

Dynamic Event-Triggered Output Feedback Control for Load Frequency Control in Power Systems With Multiple Cyber Attacks

This article presents a novel dynamic event-triggered scheme for the load frequency regulation with periodic denial-of-service (DoS) attacks and deception attacks via decentralized output-based control algorithm. Compared with the existing event-triggered strategy, the proposed one automatically changes the parameters of the triggered condition by detecting the frequency trend of the DoS attack to change the release frequency, which can ensure the stability of the power system while increasing the probability of effective transmission subject to DoS attack and thus, reducing network bandwidth usage. First, the proposed dynamic event-triggered strategy combined with the decentralized output-based controller is presented in a unified framework to deal with deception attacks and DoS attacks in the multiarea power system. Then, we utilize the Lyapunov stability theory to analyze the exponential stability in the mean-square sense and the robustness of the power system. By solving a set of linear matrix inequalities (LMIs), a procedure is given for the design of output-based load frequency controllers. Finally, a three-area power system is exploited as a simulation to verify the effectiveness of the proposed results. 

In this paper, the tracking control problem of a class of uncertain strict-feedback nonlinear systems with unknown control direction and unknown actuator fault is studied. By using the neural network control approach and dynamic surface control technique, an adaptive neural network dynamic surface control law is designed. Based on the neural network approximator, the uncertain nonlinear dynamics are approximated. Using the dynamic surface control technique, the complexity explosion problems in the design of virtual control laws and adaptive updating laws can be overcome. Moreover, to solve the unknown control direction and unknown actuator fault problems, a type of Nussbaum gain function is incorporated into the recursive design of dynamic surface control. Based on the designed adaptive control law, it can be confirmed that all of the signals in the closed-loop system are semi-global bounded, and the convergence of the tracking error to the specified small neighborhood of the origin could be ensured by adjusting the designing parameters. Finally, two examples are provided to demonstrate the effectiveness of the proposed adaptive control law. 

Adaptive neural network dynamic surface control of uncertain strict-feedback nonlinear systems with unknown control direction and unknown actuator fault

The problem of decentralized event-triggered control for a class of network-based state-dependent uncertain systems subject to network transmission delay and deception attacks is considered in this article. To reduce network load, a novel decentralized adaptive event-triggered scheme (AETS) is developed to transmit necessary sampled signals. During network transmission, a more practical deception attack phenomenon is considered, where the attack behaviors in different channels are governed by independent Bernoulli processes. Moreover, a set of improved data buffers are applied in the controller side to organize the decentralized triggered data and alleviate the impact of network transmission delay, such that the transmitted data can be utilized timely. Then, an integrated closed-loop system with state-dependent uncertainties is constructed by taking the AETS, deception attacks and data buffers into account. Sufficient conditions that guarantee the mean-square exponential stability of the closed-loop system are presented by employing the Lyapunov functional method, and the design criterion of the controller gain is given by an exact expression. Finally, the proposed method is applied to the control of electronic circuits to verify its practicability and effectiveness.

Decentralized Adaptive Event-Triggered Control for a Class of Uncertain Systems With Deception Attacks and Its Application to Electronic Circuits

The invention relates to a fisheye image distortion correction method based on a fisheye imaging model, relates to a distortion image correction method, and in particular relates to a fisheye image distortion correction method. The problem that tangential distortion cannot be corrected through the existing fisheye image correction method in a condition that internal parameters and external parameters of a lens and distortion coefficients are unknown can be solved. The fisheye image distortion correction method disclosed by the invention comprises the following steps: coordinate transformation of a fisheye image is carried out at first; assumed target image pixels are corrected in horizontal and vertical directions; then, according to the imaging law of a pinhole imaging model and the imaging features of the fisheye imaging model, the coordinate corrected target image is mapped into a fisheye image under a fisheye lens imaging model, so that correction of the image is realized; for batch images, the mapping relationship obtained in the third step is stored; the subsequently acquired fisheye image is corrected; finally, interpolation of the image after distortion correction of the fisheye image is completed is carried out; and thus, the finally processed image is obtained. The fisheye image distortion correction method disclosed by the invention is suitable for performing distortion correction of the fisheye image.

Fisheye image distortion correction method based on fisheye imaging model

The invention discloses an automatic surface mounting machine feeder element position correction device and an automatic correction method based on image processing, which relate to the automatic correction devices and methods for the surface mounting machine feeder element position and solve the problems that the existing feeder depends on manual correction or the precision is low when the initial element position is corrected mechanically. The device comprises an upper computer, a correction fixing device, an industrial camera and an LED light source, wherein the upper computer is connected with the industrial camera; the industrial camera is fixed on the correction fixing device for acquiring the position image of an element at the exit of the feeder in real time; the LED light source is located at the camera lens of the industrial camera; and the upper computer is internally provided with an automatic surface mounting machine feeder element position correction control system, the system is used for controlling the industrial camera to acquire an image, the acquired image is displayed on an image display window in real time, and after processing of the element position image and calculation of position information data, a correction command is sent to control a correction action. The device and the method of the invention are used for element position correction.

Sun Yiming

Papers

Decentralized Adaptive Event-Triggered Control for a Class of Uncertain Systems With Deception Attacks and Its Application to Electronic Circuits

Fisheye image distortion correction method based on fisheye imaging model

Automatic surface mounting machine feeder element position correction device and automatic correction method based on image processing