计算受限控制系统的一种全资源预测控制方法
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摘要
针对具有时变有限且不可预知计算资源的控制系统,提出了一种充分利用可用计算资源的预测控制策略和相应的控制器设计方法.该策略在控制系统可用计算资源充足时计算多步前向预测控制量,进而使用合适预测控制量在控制器因缺少计算资源无法运行时闭合系统,达到了在不要求额外计算资源前提下提升控制系统性能的效果.利用改进的模型预测控制方法设计了相应的控制器,并分别使用纯数值和MATLAB/Lab VIEW联合仿真算例对所提出的方法进行了验证.
A computational resource aware predictive control strategy as well as the controller design method is proposed for control systems subject to limited, time-varying and unknown computational resources. The strategy calculates multistep forward control predictions when the allocated computational resources allow so, which are then used to close the system when the available computational resources are too few to run the controller, thus enabling the improvement of the control performance at no cost of additional computational resources requirement. The controller is realized by a modified model predictive method, and both numerical simulation and MATLAB/Lab VIEW co-simulation validate the effectiveness of the proposed approach.
A computational resource aware predictive control strategy as well as the controller design method is proposed for control systems subject to limited, time-varying and unknown computational resources. The strategy calculates multistep forward control predictions when the allocated computational resources allow so, which are then used to close the system when the available computational resources are too few to run the controller, thus enabling the improvement of the control performance at no cost of additional computational resources requirement. The controller is realized by a modified model predictive method, and both numerical simulation and MATLAB/Lab VIEW co-simulation validate the effectiveness of the proposed approach.
引文
1 Wang Fei-Yue, Zhang Jun, Zhang Jun, Wang Xiao. Industrial internet of minds:concept, technology and application.Acta Automatica Sinica, 2018, 44(9):1606-1617(王飞跃,张军,张俊,王晓.工业智联网:基本概念、关键技术与核心应用.自动化学报, 2018, 44(9):1606-1617)
2 Wang B L, Kang Y, Qin J H, Li Y M. Optimization algorithms for predictive control approach to networked bilinear systems. Acta Automatica Sinica, 2017, 43(1):1234-1240
3 Stankovic J A. Research directions for the internet of things.IEEE Internet of Things Journal, 2014, 1(1):3-9
4 Xia Yuan-Qing. Cloud control systems and their challenges.Acta Automatica Sinica, 2016, 42(1):1-12(夏元清.云控制系统及其面临的挑战.自动化学报, 2016, 42(1):1-12)
5 Lu C Y, Saifullah A, Li B, Sha M, Gonzalez H, Gunatilaka D, Wu C J, Nie L S, Chen Y X. Real-time wireless sensor-actuator networks for industrial cyber-physical systems. Proceedings of the IEEE, 2016, 104(5):1013-1024
6 Saifullah A, Xu Y, Lu C Y, Chen Y X. End-to-end communication delay analysis in industrial wireless networks. IEEE Transactions on Computers, 2015, 64(5):1361-1374
7 Zhang D, Wang Q G, Yu L. Filtering and Control of Wireless Networked Systems. Springer International Publishing,2017.
8 Al-Dabbagh A W, Chen T W. Design considerations for wireless networked control systems. IEEE Transactions on Industrial Electronics, 2016, 63(9):5547-5557
9 Al-Areqi S, G′erges D, Steven L. Event-based networked control and scheduling codesign with guaranteed performance.Automatica, 2015, 57:128-134
10 Pang Z H, Liu G P, Zhou D H, Sun D H. Data-based predictive control for networked nonlinear systems with networkinduced delay and packet dropout. IEEE Transactions on Industrial Electronics, 2016, 63(2):1249-1257
11 Tan C, Yin X, Liu G P, Huang J J, Zhao Y B. Prediction based approach to output consensus of heterogeneous multi-agent systems with delays. IET Control Theory and Applications, 2018, 12(1):20-28
12 Dimarogonas D V, Johansson K H. Stability analysis for multi-agent systems using the incidence matrix:quantized communication and formation control. Automatica, 2010,46(4):695-700
13 Nunes D, Silva J S, Boavida F. A Practical Introduction to Human-in-the-Loop Cyber-Physical Systems, Willy-IEEE Press, 2018.
14 Christos G, Cassandras. Smart cities as cyber-physical social systems. Engineering, 2016, 2(2):156-158
15 Marti P, Velasco M, Fuertes J M, Camacho A, Buttazzo G. Design of an embedded control system laboratory experiment. IEEE Transactions on Industrial Electronics, 2010,57(10):3297-3307
16 Adimoolam A, Dang T, Donz′e A, Kapins J, Jin X, Classification and Coverage-based Falsification for Embedded Control Systems. Springer International Publishing, 2017. 483-503
17 Ling L, Chen C L, Hua C Q, Zhu S Y, Guan X P. Co-design of Stabilisation and transmission scheduling for wireless control systems. IET Control Theory and Applications, 2017,11(11):1767-1778
18 Henriksson E, Quevedo D E, Peters E G W, Sandberg H, Johansson K H. Multiple-loop self-triggered model predictive control for network scheduling and control. IEEE Transactions on Control Systems Technology, 2015, 23(6):2167-2181
19 Liu K, Fridman E, Johansson K H. Networked control with stochastic scheduling. IEEE Transactions on Automatic Control, 2015, 60(11):3071-3076
20 Bhattachary R, Balas G. Anytime control algorithm:model reduction approach. Journal of Guidance Control and Dynamics, 2004, 27(5):767-776
21 Xi Y G, Li D W, Lin S. Model predictive control-status and challenges. Acta Automatica Sinica, 2013, 39(3):222-236
2 Wang B L, Kang Y, Qin J H, Li Y M. Optimization algorithms for predictive control approach to networked bilinear systems. Acta Automatica Sinica, 2017, 43(1):1234-1240
3 Stankovic J A. Research directions for the internet of things.IEEE Internet of Things Journal, 2014, 1(1):3-9
4 Xia Yuan-Qing. Cloud control systems and their challenges.Acta Automatica Sinica, 2016, 42(1):1-12(夏元清.云控制系统及其面临的挑战.自动化学报, 2016, 42(1):1-12)
5 Lu C Y, Saifullah A, Li B, Sha M, Gonzalez H, Gunatilaka D, Wu C J, Nie L S, Chen Y X. Real-time wireless sensor-actuator networks for industrial cyber-physical systems. Proceedings of the IEEE, 2016, 104(5):1013-1024
6 Saifullah A, Xu Y, Lu C Y, Chen Y X. End-to-end communication delay analysis in industrial wireless networks. IEEE Transactions on Computers, 2015, 64(5):1361-1374
7 Zhang D, Wang Q G, Yu L. Filtering and Control of Wireless Networked Systems. Springer International Publishing,2017.
8 Al-Dabbagh A W, Chen T W. Design considerations for wireless networked control systems. IEEE Transactions on Industrial Electronics, 2016, 63(9):5547-5557
9 Al-Areqi S, G′erges D, Steven L. Event-based networked control and scheduling codesign with guaranteed performance.Automatica, 2015, 57:128-134
10 Pang Z H, Liu G P, Zhou D H, Sun D H. Data-based predictive control for networked nonlinear systems with networkinduced delay and packet dropout. IEEE Transactions on Industrial Electronics, 2016, 63(2):1249-1257
11 Tan C, Yin X, Liu G P, Huang J J, Zhao Y B. Prediction based approach to output consensus of heterogeneous multi-agent systems with delays. IET Control Theory and Applications, 2018, 12(1):20-28
12 Dimarogonas D V, Johansson K H. Stability analysis for multi-agent systems using the incidence matrix:quantized communication and formation control. Automatica, 2010,46(4):695-700
13 Nunes D, Silva J S, Boavida F. A Practical Introduction to Human-in-the-Loop Cyber-Physical Systems, Willy-IEEE Press, 2018.
14 Christos G, Cassandras. Smart cities as cyber-physical social systems. Engineering, 2016, 2(2):156-158
15 Marti P, Velasco M, Fuertes J M, Camacho A, Buttazzo G. Design of an embedded control system laboratory experiment. IEEE Transactions on Industrial Electronics, 2010,57(10):3297-3307
16 Adimoolam A, Dang T, Donz′e A, Kapins J, Jin X, Classification and Coverage-based Falsification for Embedded Control Systems. Springer International Publishing, 2017. 483-503
17 Ling L, Chen C L, Hua C Q, Zhu S Y, Guan X P. Co-design of Stabilisation and transmission scheduling for wireless control systems. IET Control Theory and Applications, 2017,11(11):1767-1778
18 Henriksson E, Quevedo D E, Peters E G W, Sandberg H, Johansson K H. Multiple-loop self-triggered model predictive control for network scheduling and control. IEEE Transactions on Control Systems Technology, 2015, 23(6):2167-2181
19 Liu K, Fridman E, Johansson K H. Networked control with stochastic scheduling. IEEE Transactions on Automatic Control, 2015, 60(11):3071-3076
20 Bhattachary R, Balas G. Anytime control algorithm:model reduction approach. Journal of Guidance Control and Dynamics, 2004, 27(5):767-776
21 Xi Y G, Li D W, Lin S. Model predictive control-status and challenges. Acta Automatica Sinica, 2013, 39(3):222-236