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[Keyword] networked control(11hit)

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  • Communication Quality Estimation Observer: An Approach for Integrated Communication Quality Estimation and Control for Digital-Twin-Assisted Cyber-Physical Systems Open Access

    Ryogo KUBO  

     
    INVITED PAPER

      Pubricized:
    2022/04/14
      Vol:
    E105-B No:10
      Page(s):
    1139-1153

    Cyber-physical systems (CPSs) assisted by digital twins (DTs) integrate sensing-actuation loops over communication networks in various infrastructure services and applications. This study overviews the concept, methodology, and applications of the integrated communication quality estimation and control for the DT-assisted CPSs from both communications and control perspectives. The DT-assisted CPSs can be considered as networked control systems (NCSs) with virtual dynamic models of physical entities. A communication quality estimation observer (CQEO), which is an extended version of the communication disturbance observer (CDOB) utilized for time-delay compensation in NCSs, is proposed to estimate the integrated effects of the quality of services (QoS) and cyberattacks on the NCS applications. A path diversity technique with the CQEO is also proposed to achieve reliable NCSs. The proposed technique is applied to two kinds of NCSs: remote motor control and haptic communication systems. Moreover, results of the simulation on a haptic communication system show the effectiveness of the proposed approach. In the end, future research directions of the CQEO-based scheme are presented.

  • Control Vector Selection for Extended Packetized Predictive Control in Wireless Networked Control Systems

    Keisuke NAKASHIMA  Takahiro MATSUDA  Masaaki NAGAHARA  Tetsuya TAKINE  

     
    PAPER-Network

      Pubricized:
    2020/01/15
      Vol:
    E103-B No:7
      Page(s):
    748-758

    We study wireless networked control systems (WNCSs), where controllers (CLs), controlled objects (COs), and other devices are connected through wireless networks. In WNCSs, COs can become unstable due to bursty packet losses and random delays on wireless networks. To reduce these network-induced effects, we utilize the packetized predictive control (PPC) method, where future control vectors to compensate bursty packet losses are generated in the receiving horizon manner, and they are packed into packets and transferred to a CO unit. In this paper, we extend the PPC method so as to compensate random delays as well as bursty packet losses. In the extended PPC method, generating many control vectors improves the robustness against both problems while it increases traffic on wireless networks. Therefore, we consider control vector selection to improve the robustness effectively under the constraint of single packet transmission. We first reconsider the input strategy of control vectors received by COs and propose a control vector selection scheme suitable for the strategy. In our selection scheme, control vectors are selected based on the estimated average and variance of round-trip delays. Moreover, we solve the problem that the CL may misconceive the CO's state due to insufficient information for state estimation. Simulation results show that our selection scheme achieves the higher robustness against both bursty packet losses and delays in terms of the 2-norm of the CO's state.

  • Quantized Event-Triggered Control of Discrete-Time Linear Systems with Switching Triggering Conditions

    Shumpei YOSHIKAWA  Koichi KOBAYASHI  Yuh YAMASHITA  

     
    PAPER

      Vol:
    E101-A No:2
      Page(s):
    322-327

    Event-triggered control is a method that the control input is updated only when a certain triggering condition is satisfied. In networked control systems, quantization errors via A/D conversion should be considered. In this paper, a new method for quantized event-triggered control with switching triggering conditions is proposed. For a discrete-time linear system, we consider the problem of finding a state-feedback controller such that the closed-loop system is uniformly ultimately bounded in a certain ellipsoid. This problem is reduced to an LMI (Linear Matrix Inequality) optimization problem. The volume of the ellipsoid may be adjusted. The effectiveness of the proposed method is presented by a numerical example.

  • Model Based Fallback Control for Networked Control System via Switched Lyapunov Function

    Tsubasa SASAKI  Kenji SAWADA  Seiichi SHIN  Shu HOSOKAWA  

     
    PAPER-Systems and Control

      Vol:
    E100-A No:10
      Page(s):
    2086-2094

    This paper aims to propose a Fallback Control System isolated from cyber-attacks against networked control systems. The fallback control system implements maintaining functionality after an incident. Since cyber-attacks tamper with the communication contents of the networked control systems, the fallback control system is installed in a control target side. The fallback control system detects the incident without the communication contents on field network. This system detects an incident based on a bilinear observer and a switched Lyapunov function. When an incident is detected, normal operation is switched to fallback operation automatically. In this paper, a practical experiment with Ball-Sorter simulating a simple defective discriminator as a part of Factory Automation systems is shown. Assumed cyber-attacks against Ball-Sorter are Man In The Middle attack and Denial of Service attack.

  • Symbolic Design of Networked Control Systems with State Prediction

    Masashi MIZOGUCHI  Toshimitsu USHIO  

     
    PAPER-Formal techniques

      Pubricized:
    2017/03/07
      Vol:
    E100-D No:6
      Page(s):
    1158-1165

    In this paper, we consider a networked control system where bounded network delays and packet dropouts exist in the network. The physical plant is abstracted by a transition system whose states are quantized states of the plant measured by a sensor, and a control specification for the abstracted plant is given by a transition system when no network disturbance occurs. Then, we design a prediction-based controller that determines a control input by predicting a set of all feasible abstracted states at time when the actuator receives the delayed input. It is proved that the prediction-based controller suppresses effects of network delays and packet dropouts and that the controlled plant still achieves the specification in spite of the existence of network delays and packet dropouts.

  • H-Infinity Control Design Considering Packet Loss as a Disturbance for Networked Control Systems

    Takashi OGURA  Kentaro KOBAYASHI  Hiraku OKADA  Masaaki KATAYAMA  

     
    PAPER

      Vol:
    E100-A No:2
      Page(s):
    353-360

    This paper studies H∞ control for networked control systems with packet loss. In networked control systems, packet loss is one of major weakness because the control performance deteriorates due to packet loss. H∞ control, which is one of robust control, can design a controller to reduce the influence of disturbances acting on the controlled object. This paper proposes an H∞ control design that considers packet loss as a disturbance. Numerical examples show that the proposed H∞ control design can more effectively reduce control performance deterioration due to packet loss than the conventional H∞ control design. In addition, this paper provides control performance comparisons of H∞ control and Linear Quadratic (LQ) control. Numerical examples show that the control performance of the proposed H∞ control design is better than that of the LQ control design.

  • Event-Triggered and Self-Triggered Control for Networked Control Systems Using Online Optimization

    Koichi KOBAYASHI  Kunihiko HIRAISHI  

     
    PAPER

      Vol:
    E99-A No:2
      Page(s):
    468-474

    Event-triggered and self-triggered control methods are an important control strategy in networked control systems. Event-triggered control is a method that the measured signal is sent to the controller (i.e., the control input is recomputed) only when a certain condition is satisfied. Self-triggered control is a method that the control input and the (non-uniform) sampling interval are computed simultaneously. In this paper, we propose new methods of event-triggered control and self-triggered control from the viewpoint of online optimization (i.e., model predictive control). In self-triggered control, the control input and the sampling interval are obtained by solving a pair of a quadratic programming (QP) problem and a mixed integer linear programming (MILP) problem. In event-triggered control, whether the control input is updated or not is determined by solving two QP problems. The effectiveness of the proposed methods is presented by numerical examples.

  • Networked Control System with Delay Adaptive Cyber-Physical Integration

    Chao ZHANG  Jialuo XIAO  

     
    LETTER-Systems and Control

      Vol:
    E97-A No:3
      Page(s):
    873-876

    A Networked Control System (NCS) can be considered a form of Cyber-Physical System (CPS) with its network architecture and typical features, such as delay, jitter and package loss. So far, less discussion has been carried out for NCS from the view point of CPS. In this letter, the NCS with short delay is analyzed with cyber-physical integration. The sampling rate is depicted as one of the states in the state equations. The simulation results show that the cyber-physical integration not only adjusts the sampling rate to the states of the controlled physical system, but also adapts to the delay of the network. The averaged sampling rate and the stabilization time are smaller compared with the traditional NCS.

  • Self-Triggered Model Predictive Control with Delay Compensation for Networked Control Systems

    Koichi KOBAYASHI  Kunihiko HIRAISHI  

     
    PAPER

      Vol:
    E96-A No:5
      Page(s):
    861-868

    Self-triggered control is a control method that the control input and the sampling period are computed simultaneously in sampled-data control systems, and is studied in the field of networked control systems. In this paper, a new approach for self-triggered control is proposed based on the model predictive control (MPC) method. First, self-triggered MPC with delay compensation in which the delay-compensation input is introduced is newly formulated. Next, in order to efficiently solve this MPC problem, the optimal control problem with horizon one is formulated, and an approximate solution method is derived. Finally, the effectiveness of the proposed approach is shown by a numerical example.

  • Data Rate Limitations in Feedback Control over Networks

    Hideaki ISHII  Koji TSUMURA  

     
    INVITED PAPER

      Vol:
    E95-A No:4
      Page(s):
    680-690

    This paper provides an overview on the recent research on networked control with an emphasis on the tight relation between the two fields of control and communication. In particular, we present several results focusing on data rate constraints in networked control systems, which can be modeled as quantization of control-related signals. The motivation is to reduce the amount of data rate as much as possible in obtaining control objectives such as stabilization and control performance under certain measures. We also discuss some approaches towards control problems based on techniques from signal processing and information theory.

  • Decentralized Coverage Control for Multi-Agent Systems with Nonlinear Dynamics

    Alireza DIRAFZOON  Mohammad Bagher MENHAJ  Ahmad AFSHAR  

     
    PAPER-Community

      Vol:
    E94-D No:1
      Page(s):
    3-10

    In this paper, we study the decentralized coverage control problem for an environment using a group of autonomous mobile robots with nonholonomic kinematic and dynamic constraints. In comparison with standard coverage control procedures, we develop a combined controller for Voronoi-based coverage approach in which kinematic and dynamic constraints of the actual mobile sensing robots are incorporated into the controller design. Furthermore, a collision avoidance component is added in the kinematic controller in order to guarantee a collision free coverage of the area. The convergence of the network to the optimal sensing configuration is proven with a Lyapunov-type analysis. Numerical simulations are provided approving the effectiveness of the proposed method through several experimental scenarios.