Suboptimal control for time-varying systems with stochastic communication protocol: The finite-horizon case

In this paper, the suboptimal control problem is addressed for a class of discrete time-varying systems subjected to the stochastic communication protocol (SCP). The measurements provided by the sensors are transmitted through the communication channel and then fed into the controller. The SCP is utilized to select the sensor getting access to the communication media. In presence of the nonlinearities, the accurate value of the cost function cannot be obtained. As an alternative, a certain upper bound of the cost function is employed to quantify the control performance. The main purpose of the addressed problem is to develop the time-varying control parameters such that the derived upper bound of the cost function can be minimized over the finite-horizon [0, N]. The algorithm to compute the control parameters is provided in terms of a set of backward coupled Riccati-like recursions. In the end, a numerical example is provided to verify the validity of the proposed design method.

[1]  Hao Xu,et al.  Stochastic optimal control of unknown linear networked control system in the presence of random delays and packet losses , 2012, Autom..

[2]  Lei Guo,et al.  Multi‐tasking optimal control of networked control systems: A delta operator approach , 2017 .

[3]  Mo-Yuen Chow,et al.  Optimal Stabilizing Gain Selection for Networked Control Systems With Time Delays and Packet Losses , 2009, IEEE Transactions on Control Systems Technology.

[4]  James Lam,et al.  Finite-Horizon ${\cal H}_{\infty}$ Control for Discrete Time-Varying Systems With Randomly Occurring Nonlinearities and Fading Measurements , 2015, IEEE Transactions on Automatic Control.

[5]  Lei Guo,et al.  Resilient Control of Networked Control System Under DoS Attacks: A Unified Game Approach , 2016, IEEE Transactions on Industrial Informatics.

[6]  Ling Shi,et al.  Optimal DoS Attack Scheduling in Wireless Networked Control System , 2016, IEEE Transactions on Control Systems Technology.

[7]  Wen-an Zhang,et al.  Distributed Finite-Horizon Fusion Kalman Filtering for Bandwidth and Energy Constrained Wireless Sensor Networks , 2014, IEEE Transactions on Signal Processing.

[8]  G. Nikolakopoulos,et al.  LQR-output feedback gain scheduling of mobile networked controlled systems , 2004, Proceedings of the 2004 American Control Conference.

[9]  Jianbin Qiu,et al.  A Combined Adaptive Neural Network and Nonlinear Model Predictive Control for Multirate Networked Industrial Process Control , 2016, IEEE Transactions on Neural Networks and Learning Systems.

[10]  Yang Xu,et al.  Event-Driven Control for Networked Control Systems With Quantization and Markov Packet Losses , 2017, IEEE Transactions on Cybernetics.

[11]  Wen-an Zhang,et al.  Distributed Fusion Estimation With Missing Measurements, Random Transmission Delays and Packet Dropouts , 2014, IEEE Transactions on Automatic Control.

[12]  Tamer Basar,et al.  Optimal control of LTI systems over unreliable communication links , 2006, Autom..

[13]  Xunyuan Yin,et al.  Resilient Estimation for Networked Systems With Variable Communication Capability , 2016, IEEE Transactions on Automatic Control.

[14]  Dragan Nesic,et al.  Input–Output Stability of Networked Control Systems With Stochastic Protocols and Channels , 2008, IEEE Transactions on Automatic Control.

[15]  Wen-an Zhang,et al.  Robust Information Fusion Estimator for Multiple Delay-Tolerant Sensors With Different Failure Rates , 2013, IEEE Transactions on Circuits and Systems I: Regular Papers.

[16]  Huaguang Zhang,et al.  Near-Optimal Control for Nonzero-Sum Differential Games of Continuous-Time Nonlinear Systems Using Single-Network ADP , 2013, IEEE Transactions on Cybernetics.

[17]  Emilia Fridman,et al.  A Round-Robin Type Protocol for Distributed Estimation with H∞ Consensus , 2014, Syst. Control. Lett..

[18]  Shaocheng Tong,et al.  Fuzzy Approximation-Based Adaptive Backstepping Optimal Control for a Class of Nonlinear Discrete-Time Systems With Dead-Zone , 2016, IEEE Transactions on Fuzzy Systems.

[19]  Alberto Bemporad,et al.  Stability analysis of stochastic Networked Control Systems , 2010, Proceedings of the 2010 American Control Conference.

[20]  Bruno Sinopoli,et al.  Foundations of Control and Estimation Over Lossy Networks , 2007, Proceedings of the IEEE.

[21]  Fuad E. Alsaadi,et al.  A Resilient Approach to Distributed Filter Design for Time-Varying Systems Under Stochastic Nonlinearities and Sensor Degradation , 2017, IEEE Transactions on Signal Processing.

[22]  Yan Liang,et al.  Linear-minimum-mean-square-error observer for multi-rate sensor fusion with missing measurements , 2014 .

[23]  Lei Zou,et al.  Observer-based H∞ control of networked systems with stochastic communication protocol: The finite-horizon case , 2016, Autom..

[24]  Lei Zou,et al.  Set-membership filtering for time-varying systems with mixed time-delays under Round-Robin and Weighted Try-Once-Discard protocols , 2016, Autom..