An integrated performance degradation detection and recovery scheme incorporating 2-DOF controllers for feedback control systems

For turbo-coded differential phase-shift-keying (DPSK) systems under correlated flat-fading channels, a serial iterative structure of soft-input-soft-output (SISO) forward/backward MAP (FB-MAP) detection and SISO decoder is proposed to reduce the computational complexity of MAP detection without performance degradation. The simulation results show that the FB-MAP detection scheme offers the same or better bit error rate (BER) performance with lower computational complexity when compared with the <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">a posteriori</i> probability (APP) demodulator, the SISO MAP detection, and the SISO multiple-symbol differential sphere decoder (MSDSD) scheme. Although the computational complexity is higher than the iterative filtered multiple differential detection (IF-MDD) scheme, the proposed detection scheme can have better BER performance.

Recent cyberattacks targeting process control systems have demonstrated that reliance on information technology-based approaches alone to address cybersecurity needs is insufficient and that operational technology-based solutions are needed. An attack detection scheme that monitors process operation and determines the presence of an attack represents an operational technology-based approach. Attack detection schemes may be designed to monitor a process operated at or near its steady–state to account for the typical operation of chemical processes. However, transient operation may occur; for example, during process start-up and set–point changes. Detection schemes designed or tuned for steady-state operation may raise false alarms during transient process operation. In this work, we present a reachable set-based cyberattack detection scheme for monitoring processes during transient operation. Both additive and multiplicative false data injection attacks (FDIAs) that alter data communicated over the sensor–controller and controller–actuator communication links are considered. For the class of attacks considered, the detection scheme does not raise false alarms during transient operations. Conditions for classifying attacks based on the ability of the detection scheme to detect the attacks are presented. The application of the reachable set-based detection scheme is demonstrated using two illustrative processes under different FDIAs. For the FDIAs considered, their detectability with respect to the reachable set-based detection scheme is analyzed.

A sequential two-dimensional (2D) partial response maximum likelihood (PRML) detection scheme for holographic data storage (HDS) systems is proposed. We use two complexity reduction schemes, a reduced-state trellis and a constant-weight (CW) constraint. In the reduced-state trellis, the limited candidate bits surrounding the target bit are considered for the 2D PRML detector. In the CW constraint, the trellis transitions that violate the CW condition that each code-word block has only one white bit are eliminated. However, the 2D PRML detector using the complexity reduction schemes, which operates on 47 states and 169 branches, has performance degradation. To overcome performance degradation, a sequential detection algorithm uses the estimated a priori probability. By the sequential procedure, we mitigate 2D intersymbol interference with an enhanced reliability of the branch metric. Simulation results show that the proposed 2D PRML detection scheme yields about 3 dB gains over the one-dimensional PRML detection scheme.

In WSNs, failures are unavoidable due to the inhospitable environment and unattended deployment. The node failure leads to disconnection from the network and causes network partitioning. We propose to develop a fault detection and recovery scheme where the sink generates an agent packet and the Agent forms a query path towards the dead or faulty node. Here, sink periodically broadcasts the Agent packet to all its neighbor nodes. The receiving node randomly makes a decision as whether to forward the packet or not thereby detecting the dead or faulty nodes. After detecting a node failure or dead node, the connectivity is restored using Least-Disruptive Topology Repair (LeDiR) without extending the length of the shortest path among nodes compared to the pre failure topology. LeDiR replaces the faulty node with block movement.

Recently, two degrees-of-freedom (2DOF) control has been widely recognized to be efficient. The major merit of 2DOF control is independence between tracking performance and the feedback performance. However, there is a limitation on tracking performance in the 2DOF control system. In this paper, we propose a new control system that consists of a conventional 2DOF controller and a learning controller. The role of the learning controller is to realize high tracking performance, which cannot be realized alone by the 2DOF controller. The learning controller can be designed by using only information specifying a 2DOF controller, and it does not need information about the controlled plant. We show some experimental results to verify the effectiveness of the proposed system. © 1999 Scripta Technica, Electr Eng Jpn, 128(4): 102–110, 1999

The safety and security of load frequency control (LFC) system are menaced by cyber attacks and physical attacks. Sophisticated attackers can launch cyber-physical attacks (CPAs), in which cyber attacks are used to increase the impacts of physical attacks by sending wrong instructions to the LFC controller. Considering that parameters of cyber attacks in CPAs may be either fixed or variable, a novel detection scheme is designed against two potential CPAs on an LFC system, namely fixed cyber-physical attacks (FCPAs) and variable cyber-physical attacks (VCPAs), respectively. As for FCPAs, dynamic characteristics of Area Control Error (ACE) are utilized to detect the compromised data. Compared with FCPAs, VCPAs are more deceptive. A relation-based (RB) feature extraction method is introduced to distinguish the signals compromised by VCPAs from the normal ones. A detection model that does not require compromised samples is developed with the aid of support vector domain description. In the end, a comprehensive detection scheme is designed to detect both FCPAs and VCPAs on the LFC system.

In this paper, an adaptive feedback-based stable fault detection scheme is developed for linear time-invariant systems with sensor uncertainties and system parameter uncertainties. A parametric sensor uncertainty model with additive faults and multiplicative faults is introduced. To employ the model-based fault detection method, the sensor dynamics is derived. Based on the newly developed sensor dynamic models, a set of estimation model systems are established to estimate the sensor signals. Unlike most fault detection schemes which operate under the assumption that all system signals remain bounded under sensor uncertainty conditions, the adaptive sensor detection scheme proposed in this paper is integrated with an adaptive feedback controller which is designed to ensure the desired signal boundedness requirement needed for stable sensor uncertainty detection operation. By observing residuals between the sensor signals and the estimation model signals, the sensor uncertainty can be detected and specific uncertainty patterns can be identified. Desired adaptive sensor uncertainty detection performance is demonstrated in the simulation study for a linearized longitudinal aircraft flight control system.

In the last few decades, the stabilization in stationary states has emerged as a new auspicious campaigner in chaos theory and found a celebrated place through various control techniques such as predictive control, delayed feedback control, constant proportional feedback control and oscillating feedback control system. Generally, it is accepted that the superiority of control systems is not only to quash the irregular distribution of stationary states, but also to illustrate its basin of attractions as large as possible depending on the numerical as well as analytical observance. In this article, the universal stabilization in unstable stationary states is studied through superior fixed point feedback control system for a family of one-dimensional maps. Further, it is interesting to know that the novel system provides freedom in the control parameter γ due to which the stabilization increases more rapidly for the lager range of parameter γ in [0,1]. The analytical as well as numerical simulations are demonstrated to examine the behavior of parameter γ for which the unstable stationary state admits universal stability.

This work is concerned with the existence of asymptotically stable 2-D (2-dimensional) systems by means of a feedback control model represented by the system of partial difference equations and their Lagrange solutions. Thus, the goal is to establish a controller that provides a feedback control system with state variables depending solely on its Lagrange solution in the sense that the solution to the variable state is not a linear combination of other Lagrange solutions. Roughly speaking, the results showed that, to achieve such a control system, the controller has to diagonalize the block matrices of the matrices composing the system description model. Finally, a numerical example is presented to show how the controller is designed in order to generate a stable feedback control with given Lagrange solutions.

Feedback control has become a crucial tool in the research on magnetic confinement of plasmas for achieving controlled nuclear fusion. This thesis presents a novel plasma feedback control system that, for the first time, employs a Graphics Processing Unit (GPU) for microsecond-latency, real-time control computations. This novel application area for GPU computing is opened up by a new system architecture that is optimized for low-latency computations on less than kilobyte sized data samples as they occur in typical plasma control algorithms. In contrast to traditional GPU computing approaches that target complex, high-throughput computations with massive amounts of data, the architecture presented in this thesis uses the GPU as the primary processing unit rather than as an auxiliary of the CPU, and data is transferred from A-D/D-A converters directly into GPU memory using peer-to-peer PCI Express transfers. The described design has been implemented in a new, GPU-based control system for the High-Beta Tokamak – Extended Pulse (HBT-EP) device. The system is built from commodity hardware and uses an NVIDIA GeForce GPU and D-TACQ A-D/D-A converters providing a total of 96 input and 64 output channels. The system is able to run with sampling periods down to 4 μs and latencies down to 8 μs. The GPU provides a total processing power of 1.5 x 1012 floating point operations per second. To illustrate the performance and versatility of both the general architecture and concrete implementation, a new control algorithm has been developed. The algorithm is designed for the control of multiple rotating magnetic perturbations in situations where the plasma equilibrium is not known exactly and features an adaptive system model: instead of requiring the rotation frequencies and growth rates embedded in the system model to be set a priori, the adaptive algorithm derives these parameters from the evolution of the perturbation amplitudes themselves. This results in non-linear control computations with high computational demands, but is handled easily by the GPU based system. Both digital processing latency and an arbitrary multi-pole response of amplifiers and control coils is fully taken into account for the generation of control signals. To separate sensor signals into perturbed and equilibrium components without knowledge of the equilibrium fields, a new separation method based on biorthogonal decomposition is introduced and used to derive a filter that performs the separation in real-time. The control algorithm has been implemented and tested on the new, GPU-based feedback control system of the HBT-EP tokamak. In this instance, the algorithm was set up to control four rotating n = 1 perturbations at different poloidal angles. The perturbations were treated as coupled in frequency but independent in amplitude and phase, so that the system effectively controls a helical n = 1 perturbation with unknown poloidal spectrum. Depending on the plasma's edge safety factor and rotation frequency, the control system is shown to be able to suppress the amplitude of the dominant 8 kHz mode by up to 60% or amplify the saturated amplitude by a factor of up to two. Intermediate feedback phases combine suppression and amplification with a speed up or slow down of the mode rotation frequency. Increasing feedback gain results in the excitation of an additional, slowly rotating 1.4 kHz mode without further effects on the 8 kHz mode. The feedback performance is found to exceed previous results obtained with an FPGA- and Kalman-filter based control system without requiring any tuning of system model parameters. Experimental results are compared with simulations based on a combination of the Boozer surface current model and the Fitzpatrick-Aydemir model. Within the subset of phenomena that can be represented by the model as well as determined experimentally, qualitative agreement is found.

&lt;div class="section abstract"&gt;&lt;div class="htmlview paragraph"&gt;Ice buildup in the compressor section of a commercial aircraft gas turbine engine can cause a number of engine failures. One of these failure modes is known as engine rollback: an uncommanded decrease in thrust accompanied by a decrease in fan speed and an increase in turbine temperature. This paper describes the development of a model which simulates the system level impact of engine icing using the Commercial Modular Aero-Propulsion System Simulation 40k (C-MAPSS40k). When an ice blockage is added to C-MAPSS40k, the control system responds in a manner similar to that of an actual engine, and, in cases with severe blockage, an engine rollback is observed. Using this capability to simulate engine rollback, a proof-of-concept detection scheme is developed and tested using only typical engine sensors. This paper concludes that the engine control system's limit protection is the proximate cause of iced engine rollback and that the controller can detect the buildup of ice particles in the compressor section. This work serves as a feasibility study for continued research into the detection and mitigation of engine rollback using the propulsion control system.&lt;/div&gt;&lt;/div&gt;

Multiple DSP system for real time parallel processing and feedback control on fusion experiments

In this paper, an effect of control frequency for DRL-based feedback control of flow separation over NACA0012 airfoil is numerically investigated. DBD plasma actuator (DBDPA) is used as a flow control device and the flow condition is $Re=6.6\times10^4$ and the attack of angle is $15^\circ$. The feedback controller is constructed with a deep neural network and trained using Ape-X DQN, the deep reinforcement learning method. In our feedback control system, the controller gets the time history of the pressure data on the suction surface as input and determines the driving parameter of the DBD plasma actuator. As a result, the high-frequency control system (25 steps per advection time) and the normal-frequency control system (1 step per advection time) obtained a similar control strategy. And it became clear that utilizing the span-wise large vortex generated just after the DBDPA switched ON in a separated flow field is a common control method in 2 frequency controllers.

This contribution outlines the design of electric vehicle direct-current (DC) bus control system supplied by a battery/ultracapacitor hybrid energy storage system, and its coordination with the fully electrified vehicle driveline control system. The control strategy features an upper-level DC bus voltage feedback controller and a direct load compensator for stiff tracking of variable (speed-dependent) voltage target. The inner control level, comprising dedicated battery and ultracapacitor current controllers, is commanded by an intermediate-level control scheme which dynamically distributes the upper-level current command between the ultracapacitor and the battery energy storage systems. The feedback control system is designed and analytical expressions for feedback controller parameters are obtained by using the damping optimum criterion. The proposed methodology is verified by means of simulations and experimentally for different realistic operating regimes, including electric vehicle DC bus load step change, hybrid energy storage system charging/discharging, and electric vehicle driveline subject to New European Driving Cycle (NEDC), Urban Driving Dynamometer Schedule (UDDS), New York Certification Cycle (NYCC) and California Unified Cycle (LA92), as well as for abrupt acceleration/deceleration regimes.

Robust tracking control for vehicle electronic throttle using adaptive dynamic sliding mode and extended state observer