Encrypted Model Predictive Control of Nonlinear Systems

被引:0
|
作者
Suryavanshi, Atharva V. [1 ]
Alnajdi, Aisha [2 ]
Alhajeri, Mohammed S. [1 ]
Abdullah, Fahim [1 ]
Christofides, Panagiotis D. [1 ,2 ]
机构
[1] Univ Calif Los Angeles, Dept Chem & Biomol Engn, Los Angeles, CA 90095 USA
[2] Univ Calif Los Angeles, Dept Elect & Comp Engn, Los Angeles, CA 90095 USA
关键词
STABILIZATION; ALGORITHM; MPC;
D O I
10.1109/MED59994.2023.10185646
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In recent years, cyber-security of networked control systems has become crucial, as these systems are vulnerable to targeted cyber-attacks that compromise the stability, integrity and safety of these systems. In this work, secure and private communication links are established between sensor-controller and controller-actuator elements using semi-homomorphic encryption to ensure cyber-security in Model Predictive Control (MPC) of nonlinear systems. Specifically, Paillier Cryptosystem is implemented for encryption-decryption operations in the communication links. Cryptosystems, in general, work on a subset of integers. As a direct consequence of this nature of encryption algorithms, quantization errors arise in the closed-loop MPC of non-linear systems. Thus, the closed-loop encrypted MPC is designed with a certain degree of robustness to the quantization errors. Furthermore, the trade-off between the accuracy of the encrypted MPC and the computational cost is discussed. Finally, a multi-input multi-output continuous stirred tank reactor (CSTR) example is presented to demonstrate the implementation of the proposed encrypted MPC design.
引用
收藏
页码:904 / 911
页数:8
相关论文
共 50 条
  • [1] Encrypted distributed model predictive control of nonlinear processes
    Kadakia, Yash A.
    Abdullah, Fahim
    Alnajdi, Aisha
    Christofides, Panagiotis D.
    [J]. CONTROL ENGINEERING PRACTICE, 2024, 145
  • [2] Encrypted decentralized model predictive control of nonlinear processes with delays
    Kadakia, Yash A.
    Alnajdi, Aisha
    Abdullah, Fahim
    Christofides, Panagiotis D.
    [J]. CHEMICAL ENGINEERING RESEARCH & DESIGN, 2023, 200 : 312 - 324
  • [3] Encrypted Model Predictive Control of a Nonlinear Chemical Process Network
    Kadakia, Yash A.
    Suryavanshi, Atharva
    Alnajdi, Aisha
    Abdullah, Fahim
    Christofides, Panagiotis D.
    [J]. PROCESSES, 2023, 11 (08)
  • [4] Encrypted distributed model predictive control with state estimation for nonlinear processes
    Kadakia, Yash A.
    Alnajdi, Aisha
    Abdullah, Fahim
    Christofides, Panagiotis D.
    [J]. DIGITAL CHEMICAL ENGINEERING, 2023, 9
  • [5] Model predictive control with internal model for nonlinear systems
    Magni, L
    Scattolini, R
    [J]. NONLINEAR CONTROL SYSTEMS 2001, VOLS 1-3, 2002, : 621 - 626
  • [6] Model predictive control for nonlinear unsymmetrical systems
    Luo, Xiong-Lin
    Wei, Ming-Hui
    Xu, Feng
    Feng, Ai-Xiang
    [J]. Kongzhi yu Juece/Control and Decision, 2013, 28 (05): : 763 - 768
  • [7] Robust model predictive control for nonlinear systems
    Zhang Jun
    Wang Biao
    [J]. PROCEEDINGS OF THE 24TH CHINESE CONTROL CONFERENCE, VOLS 1 AND 2, 2005, : 1127 - 1131
  • [8] Multiple Model Predictive Control of Nonlinear Systems
    Kuure-Kinsey, Matthew
    Bequette, B. Wayne
    [J]. NONLINEAR MODEL PREDICTIVE CONTROL: TOWARDS NEW CHALLENGING APPLICATIONS, 2009, 384 : 153 - 165
  • [9] Robust Model Predictive Control for Nonlinear Systems
    Li, Yang
    Qiu, YuanYing
    Zhang, Jun
    [J]. ADVANCES IN COMPUTER SCIENCE, INTELLIGENT SYSTEM AND ENVIRONMENT, VOL 2, 2011, 105 : 231 - +
  • [10] Model predictive control of linear systems with nonlinear terminal control
    Chen, WH
    Hu, XB
    [J]. INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL, 2004, 14 (04) : 327 - 339