Kang K. Yen

Preventing Time-Delay Switch Attack on Load Frequency Control in Distributed Power Systems

A time-delay switch (TDS) attack on a control system is caused by adversaries that strategically imbed time delays into such systems. TDS attacks can make a control system, or more specifically a distributed power control system, unstable. Time delays can be introduced in the sensing loop (SL) or control lines. This paper describes a novel, simple, and effective method to thwart TDS attacks on SL. The proposed method works by augmenting the controller with a time-delay estimator to estimate any time delays. The modified controller controls the system under TDS attack. Also, the time-delay estimator will track time delays introduced by an adversary using a modified model reference control with an indirect supervisor and a modified least mean square minimization technique.

Neural adaptive observer-based sensor and actuator fault detection in nonlinear systems: Application in UAV

A new online detection strategy is developed to detect faults in sensors and actuators of unmanned aerial vehicle (UAV) systems. In this design, the weighting parameters of the Neural Network (NN) are updated by using the Extended Kalman Filter (EKF). Online adaptation of these weighting parameters helps to detect abrupt, intermittent, and incipient faults accurately. We apply the proposed fault detection system to a nonlinear dynamic model of the WVU YF-22 unmanned aircraft for its evaluation. The simulation results show that the new method has better performance in comparison with conventional recurrent neural network-based fault detection strategies.

Delayed inputs attack on load frequency control in smart grid

Current smart power grids have open communication infrastructures to improve efficiency, reliability and sustainability of supply. However, their open communication architecture makes them vulnerable to cyber-attacks with potentially catastrophic consequences. Here for the first time, we propose a time-delay-switch (TDS) attack by introducing time delays in the dynamics of power systems. Such an attack will have devastating consequences on smart grids if no prevention measures are considered in the design of these power systems. We considered how a TDS attack affects the dynamic performance of a power system. To do this, we first formulated a state space model of a smart power grid system under TDS attack using a hybrid systems approach. Second, we prove by analysis and demonstrate by simulation examples how a TDS attack can be used to sabotage and destabilize a smart grid.

A fuzzy extension of VIKOR for target network selection in heterogeneous wireless environments

Abstract In a highly integrated ubiquitous wireless environment, the selection of a network that can fulfill end-users’ service requests while keeping their overall satisfaction at a high level, is vital. The wrong selection can lead to undesirable conditions such as unsatisfied users, weak Quality of Service (QoS), network congestions, dropped and/or blocked calls, and wastage of valuable network resources. The selection of these networks is performed during the handoff process when a Mobile Station (MS) switches its current Point of Attachment (PoA) to a different network due to the degradation or complete loss of signal and/or deterioration of the provided QoS. Traditional schemes perform the handoff necessity estimation and trigger the network selection process based on a single metric such as Received Signal Strength (RSS). These schemes are not efficient enough, as they do not take into consideration the traffic characteristics, user preferences, network conditions and other important system metrics. This paper presents a novel multi-attribute vertical handoff algorithm for heterogeneous wireless networks which achieves seamless mobility while maximizing end-users’ satisfaction. Two modules are designed to estimated the necessity of handoff and to select the target network. These modules utilize parallel Fuzzy Logic Controllers (FLCs) with reduced rule-set in combination with a network ranking algorithm developed based on Fuzzy VIKOR (FVIKOR). Simulation results are provided and compared with a benchmark.

A fuzzy MADM ranking approach for vertical mobility in next generation hybrid networks

The wireless technologies in a heterogeneous wireless network usually differ in terms of, but not limited to, their offered bandwidths, operating frequencies and costs, coverage areas, and latencies. Currently, no single wireless technology claims to provide cost-effective services, which offers high bandwidths and low latencies to all mobile users in a large coverage area. This is where the need for well-organized vertical handoffs (VHOs) between heterogeneous wireless technologies become evident. This paper presents a new VHO algorithm which takes into account a complete set of system attributes to fulfill two tasks. The first task is to perform the VHO Necessity Estimation (VHONE) utilizing several parallel Fuzzy Logic Controllers (FLCs) with reduced rule sets to estimate the VHO necessity. The second task is the selection of the best network as the target for VHO, where a ranking algorithm is developed based on TOPSIS. Priority Weights for the different system attributes are calculated based on a Fuzzy Analytical Hierarchy Process (FAHP). Later, simulations based on four traffic classes (conversational, streaming, background, and interactive) in the presence of three wireless networks (WLAN, WMAN, and WWAN), are carried out using a comprehensive wireless simulation test-bed that contains all the necessary Radio Resource Management (RRM) modules.

Design of a High-Voltage Piezoelectric Converter for Airbag Ignition Modules

Due to the requirements for high reliability and accuracy, safety issues for airbag ignition systems need to be studied. In this paper, a high-voltage piezoelectric converter is designed to improve these requirements in airbag ignition systems. The proposed converter includes an inverter drive circuit, a Rosen piezoelectric transformer (PZT), an output circuit and a feedback control circuit. The key components of the high-voltage piezoelectric transformer are analyzed in detail. In addition, the proposed converter system is simulated and implemented for testing. The experimental results show that when the power supply is turned on, the charging time is less than 800ms. Furthermore, the output voltage of this converter can be kept between 2.9kV and 3.1kV, under high-efficiency constant current charging mode and zero-voltage switching conditions.

Active/Reactive Power Control of Three Phase Grid Connected Current Source Boost Inverter Using Particle Swarm Optimization

PID control is the most common and simplest control method used for system control. However, selecting PID control coefficients for an optimal performance in power system applications is a central problem that few have addressed. Here, we propose the use of the particle swarm optimization (PSO) method to search for the optimal parameters of a PI controller. We applied this method to design an optimal PI controller for active and reactive power in a three phase grid connected current source boot inverter (CSBI). Simulation results show that our PSO-PI parameters selection method leads to better performance.

Resilient Design of Networked Control Systems Under Time Delay Switch Attacks, Application in Smart Grid

Industrial control systems are distributed hierarchical networks that share information via an assortment of communication protocols. Such systems are vulnerable to attacks that can cause disastrous consequences. This article focuses on time delay switch (TDS) attacks and shows that cryptographic solutions are ineffective in recovering from the denial of service component of TDS attacks. Therefore, a cryptography-free TDS recovery (CF-TDSR) communication protocol enhancement is developed that leverages adaptive channel redundancy techniques and a novel state estimator, to detect and recover from the destabilizing effects of TDS attacks. Simulation results are conducted to prove that CF-TDSR ensures the control stability of linear time invariant systems and to show the efficacy of CF-TDSR against attacks deployed on multi-area load frequency control components of a distributed power grid.

Sensorimotor control: computing the immediate future from the delayed present

BackgroundThe predictive nature of the primate sensorimotor systems, for example the smooth pursuit system and their ability to compensate for long delays have been proven by many physiological experiments. However, few theoretical models have tried to explain these facts comprehensively. Here, we propose a sensorimotor learning and control model that can be used to (1) predict the dynamics of variable time delays and current and future sensory states from delayed sensory information; (2) learn new sensorimotor realities; and (3) control a motor system in real time.ResultsThis paper proposed a new time-delay estimation method and developed a computational model for a predictive control solution of a sensorimotor control system under time delay. Simulation experiments are used to demonstrate how the proposed model can explain a sensorimotor system’s ability to compensate for delays during online learning and control. To further illustrate the benefits of the proposed time-delay estimation method and predictive control in sensorimotor systems a simulation of the horizontal Vestibulo-Ocular Reflex (hVOR) system is presented.Without the proposed time-delay estimation and prediction, the hVOR can be unstable and could be affected by high frequency oscillations. These oscillations are reminiscent of a fast correction mechanism, e.g., a saccade to compensate for the hVOR delays. Comparing results of the proposed model with those in literature, it is clear that the hVOR system with impaired time-delay estimation or impaired sensory state predictor can mimic certain outcomes of sensorimotor diseases. Even more, if the control of hVOR is augmented with the proposed time-delay estimator and the predictor for eye position relative to the head, then hVOR control system can be stabilized.ConclusionsThree claims with varying degrees of experimental support are proposed in this paper. Firstly, the brain or any sensorimotor system has time-delay estimation circuits for the various sensorimotor control systems. Secondly, the brain continuously estimates current/future sensory states from the previously sensed states. Thirdly, the brain uses predicted sensory states to perform optimal motor control.

Time-delay analysis on grid-connected three-phase current source inverter based on SVPWM switching pattern

Time delays exist in most of the electronic components, digital controllers and DSPs. Certain values of time delay can easily corrupt the performance of a power control system. This time delay can strictly disturb the system dynamic in power control applications with low to medium switching frequency. In this paper, we overcome the effect of time delay in an SVPWM based switching pattern for a grid connected three-phase current source inverter. The time delay is tracked in real time and the states of the system are estimated. Our experimental results clearly show that the proposed approach can compensate the effect of the time delay and improve the quality of the performance.