Data-based predictive control for networked non-linear systems with two-channel packet dropouts

This study is concerned with the data-based control of networked non-linear control systems with random packet dropouts in both the sensor-to-controller and controller-to-actuator channels. By taking advantage of the characteristics of networked control systems such as the packet-based transmission, timestamp technique, as well as smart sensor and actuator, a data-based networked predictive control (DBNPC) method is proposed to actively compensate for the two-channel packet dropouts, where only the input and output data of the non-linear plant are required. A sufficient condition for the stability of the closed-loop system is developed. Furthermore, the resulting DBNPC system can achieve a zero steady-state output tracking error for step commands. Finally, extensive simulation results on a networked non-linear system demonstrate the effectiveness of the proposed method.

[1]  Yuanqing Xia,et al.  Data-driven predictive control for networked control systems , 2013, Inf. Sci..

[2]  Chen Peng,et al.  New study of controller design for networked control systems , 2010 .

[3]  Thomas Parisini,et al.  Networked Predictive Control of Uncertain Constrained Nonlinear Systems: Recursive Feasibility and Input-to-State Stability Analysis , 2011, IEEE Transactions on Automatic Control.

[4]  Donghua Zhou,et al.  Output Tracking Control for Networked Systems: A Model-Based Prediction Approach , 2014, IEEE Transactions on Industrial Electronics.

[5]  Sergio M. Savaresi,et al.  Non-iterative direct data-driven controller tuning for multivariable systems: theory and application , 2012 .

[6]  Zhuo Wang,et al.  From model-based control to data-driven control: Survey, classification and perspective , 2013, Inf. Sci..

[7]  Ahmet Onat,et al.  Control Over Imperfect Networks: Model-Based Predictive Networked Control Systems , 2011, IEEE Transactions on Industrial Electronics.

[8]  Sebastián Dormido,et al.  Co-design strategy of networked control systems for treacherous network conditions , 2011 .

[9]  Yuanqing Xia,et al.  Predictive control of networked systems with random delay and data dropout , 2009 .

[10]  Shangtai Jin,et al.  A Novel Data-Driven Control Approach for a Class of Discrete-Time Nonlinear Systems , 2011, IEEE Transactions on Control Systems Technology.

[11]  Feng Xia,et al.  Predictive compensation for variable network delays and packet losses in networked control systems , 2012, Comput. Chem. Eng..

[12]  Jonas Balderud,et al.  Data-driven adaptive model-based predictive control with application in wastewater systems , 2011 .

[13]  Daniel E. Quevedo,et al.  Packetized Predictive Control of Stochastic Systems Over Bit-Rate Limited Channels With Packet Loss , 2011, IEEE Transactions on Automatic Control.

[14]  Steven X. Ding,et al.  Real-Time Implementation of Fault-Tolerant Control Systems With Performance Optimization , 2014, IEEE Transactions on Industrial Electronics.

[15]  Özgür Gürbüz,et al.  Wireless Model-Based Predictive Networked Control System Over Cooperative Wireless Network , 2011, IEEE Transactions on Industrial Informatics.

[16]  Fuwen Yang,et al.  Data-driven subspace-based adaptive fault detection for solar power generation systems , 2013 .

[17]  Guo-Ping Liu,et al.  Design and Implementation of Secure Networked Predictive Control Systems Under Deception Attacks , 2012, IEEE Transactions on Control Systems Technology.

[18]  Guo-Ping Liu,et al.  Improved predictive control approach to networked control systems , 2008 .

[19]  Mo-Yuen Chow,et al.  Networked Control System: Overview and Research Trends , 2010, IEEE Transactions on Industrial Electronics.

[20]  Peng Shi,et al.  A Novel Model-Free Adaptive Control Design for Multivariable Industrial Processes , 2014, IEEE Transactions on Industrial Electronics.

[21]  Xuhui Bu,et al.  Model-Free Adaptive Control Algorithm with Data Dropout Compensation , 2012 .

[22]  Daniel E. Quevedo,et al.  Sparse Packetized Predictive Control for Networked Control Over Erasure Channels , 2013, IEEE Transactions on Automatic Control.

[23]  Di Wu,et al.  Robust predictive control for networked control and application to DC-motor control , 2014 .

[24]  Ping Zhang,et al.  A comparison study of basic data-driven fault diagnosis and process monitoring methods on the benchmark Tennessee Eastman process , 2012 .

[25]  Huiping Li,et al.  Network-Based Predictive Control for Constrained Nonlinear Systems With Two-Channel Packet Dropouts , 2014, IEEE Transactions on Industrial Electronics.

[26]  João Pedro Hespanha,et al.  A Survey of Recent Results in Networked Control Systems , 2007, Proceedings of the IEEE.

[27]  Wei Wang,et al.  Input-to-State Stability for Networked Predictive Control With Random Delays in Both Feedback and Forward Channels , 2014, IEEE Transactions on Industrial Electronics.

[28]  Xuhui Bu,et al.  Robust model free adaptive control with measurement disturbance , 2012 .

[29]  Huijun Gao,et al.  Network-Induced Constraints in Networked Control Systems—A Survey , 2013, IEEE Transactions on Industrial Informatics.

[30]  Yuan-ming Liu,et al.  Robust predictive tracking control of networked control systems with time-varying delays and data dropouts , 2013 .

[31]  Amir Hossein Davaie Markazi,et al.  Variable Selective Control Method for Networked Control Systems , 2013, IEEE Transactions on Control Systems Technology.

[32]  Xuhui Bu,et al.  Model free adaptive control with data dropouts , 2011, Expert Syst. Appl..

[33]  Daniel E. Quevedo,et al.  Robust stability of packetized predictive control of nonlinear systems with disturbances and Markovian packet losses , 2012, Autom..