Biblio
Cyber-Physical Systems (CPS) are playing important roles in the critical infrastructure now. A prominent family of CPSs are networked control systems in which the control and feedback signals are carried over computer networks like the Internet. Communication over insecure networks make system vulnerable to cyber attacks. In this article, we design an intrusion detection and compensation framework based on system/plant identification to fight covert attacks. We collect error statistics of the output estimation during the learning phase of system operation and after that, monitor the system behavior to see if it significantly deviates from the expected outputs. A compensating controller is further designed to intervene and replace the classic controller once the attack is detected. The proposed model is tested on a DC motor as the plant and is put against a deception signal amplification attack over the forward link. Simulation results show that the detection algorithm well detects the intrusion and the compensator is also successful in alleviating the attack effects.
Conducted emission of motors is a domain of interest for EMC as it may introduce disturbances in the system in which they are integrated. Nevertheless few publications deal with the susceptibility of motors, and especially, servomotors despite this devices are more and more used in automated production lines as well as for robotics. Recent papers have been released devoted to the possibility of compromising such systems by cyber-attacks. One could imagine the use of smart intentional electromagnetic interference to modify their behavior or damage them leading in the modification of the industrial process. This paper aims to identify the disturbances that may affect the behavior of a Commercial Off-The-Shelf servomotor when exposed to an electromagnetic field and the criticality of the effects with regards to its application. Experiments have shown that a train of radio frequency pulses may induce an erroneous reading of the position value of the servomotor and modify in an unpredictable way the movement of the motor's axis.
This paper develops a model for Wells turbine using Xilinx system generator (XSG)toolbox of Matlab. The Wells turbine is very popular in oscillating water column (OWC) wave energy converters. Mostly, the turbine behavior is emulated in a controlled DC or AC motor coupled with a generator. Therefore, it is required to model the OWC and Wells turbine in real time software like XSG. It generates the OWC turbine behavior in real time. Next, a PI control scheme is suggested for controlling the DC motor so as to emulate the Wells turbine efficiently. The overall performance of the system is tested with asquirrel cage induction generator (SCIG). The Pierson-Moskowitz and JONSWAP irregular wave models have been applied to validate the OWC model. Finally, the simulation results for Wells turbine and PI controller have beendiscussed.
With the application and promotion of electric vehicles, vehicle security problems caused by actuator reliability have become increasingly prominent. Firstly, the paper analyses and sums motor failure modes and their effects of permanent magnet synchronous motor (PMSM) , which is commonly used on electric vehicles. And then design a hierarchical structure of the vehicle control strategies and the corresponding algorithms, and adjust based on the different failure modes. Finally conduct simulation conditions in CarSim environment. Verify the control strategy and algorithm can maintain vehicle stability and reduce the burden on driver under motor failure conditions.