Input-to-State Stability of Perturbed Nonlinear Systems With Event-Triggered Receding Horizon Control Scheme

In this paper, input-to-state stability (ISS) properties of perturbed systems with event-triggered receding horizon control (RHC) schemes are studied. Two event-triggered control schemes, which are the event-triggered quasi-infinite RHC (EQRHC) and the event-triggered dual-mode RHC (EDRHC) strategies, respectively, are considered. In the EQRHC scheme, an optimal control problem (OCP) should be considered at triggering time and the event is triggered if the error between the actual system state and the optimal system state violating a threshold. While in the EDRHC strategy, an OCP is only solved outside the terminal region and a local control law will be used inside the terminal region. The corresponding event condition is redesigned based on if the system state enters the terminal region or not. The event-triggering condition outside the terminal region is the same with that of the EQRHC scheme and the event-triggering condition inside the terminal region is proposed based on the difference between the actual system state and the predictive system state. Sufficient conditions of feasibility are proposed and ISS properties of both event-triggered control schemes are studied, respectively. At last, numerical simulations show the validity of the proposed methods.

[1]  Chen Peng,et al.  Event-triggered communication and H∞H∞ control co-design for networked control systems , 2013, Autom..

[2]  Huiping Li,et al.  Periodic event-triggering in distributed receding horizon control of nonlinear systems , 2015, Syst. Control. Lett..

[3]  Dimos V. Dimarogonas,et al.  Event-Triggered Strategies for Decentralized Model Predictive Controllers , 2011 .

[4]  Dimos V. Dimarogonas,et al.  Novel event-triggered strategies for Model Predictive Controllers , 2011, IEEE Conference on Decision and Control and European Control Conference.

[5]  Huiping Li,et al.  Event-triggered robust model predictive control of continuous-time nonlinear systems , 2014, Autom..

[6]  Ning He,et al.  Event-Based Robust Sampled-Data Model Predictive Control: A Non-Monotonic Lyapunov Function Approach , 2015, IEEE Transactions on Circuits and Systems I: Regular Papers.

[7]  Eduardo Sontag Input to State Stability: Basic Concepts and Results , 2008 .

[8]  Thomas Parisini,et al.  Robust Model Predictive Control of Nonlinear Systems With Bounded and State-Dependent Uncertainties , 2009, IEEE Transactions on Automatic Control.

[9]  Jing Zhang,et al.  Two triggered information transmission algorithms for distributed moving horizon state estimation , 2014, Syst. Control. Lett..

[10]  Antonella Ferrara,et al.  Robust Model Predictive Control With Integral Sliding Mode in Continuous-Time Sampled-Data Nonlinear Systems , 2011, IEEE Transactions on Automatic Control.

[11]  Dimos V. Dimarogonas,et al.  Event-triggered intermittent sampling for nonlinear model predictive control , 2017, Autom..

[12]  Riccardo Scattolini,et al.  Regional Input-to-State Stability for Nonlinear Model Predictive Control , 2006, IEEE Transactions on Automatic Control.

[13]  Peng Shi,et al.  Network-Based Event-Triggered Control for Singular Systems With Quantizations , 2016, IEEE Transactions on Industrial Electronics.

[14]  Dimos V. Dimarogonas,et al.  Distributed aperiodic model predictive control for multi-agent systems , 2015 .

[15]  Jing Zhang,et al.  Economic model predictive control with triggered evaluations: State and output feedback , 2014 .

[16]  Qing-Long Han,et al.  On Designing a Novel Self-Triggered Sampling Scheme for Networked Control Systems With Data Losses and Communication Delays , 2016, IEEE Transactions on Industrial Electronics.

[17]  Dong Yue,et al.  A Delay System Method for Designing Event-Triggered Controllers of Networked Control Systems , 2013, IEEE Transactions on Automatic Control.

[18]  Riccardo Scattolini,et al.  A stabilizing model-based predictive control algorithm for nonlinear systems , 2001, Autom..

[19]  D. Limón,et al.  Input-to-state stable MPC for constrained discrete-time nonlinear systems with bounded additive uncertainties , 2002, Proceedings of the 41st IEEE Conference on Decision and Control, 2002..

[20]  David Q. Mayne,et al.  Model predictive control: Recent developments and future promise , 2014, Autom..

[21]  Antonella Ferrara,et al.  Asynchronous Networked MPC With ISM for Uncertain Nonlinear Systems , 2017, IEEE Transactions on Automatic Control.

[22]  Yisheng Zhong,et al.  Robust Attitude Regulation of a 3-DOF Helicopter Benchmark: Theory and Experiments , 2011, IEEE Transactions on Industrial Electronics.

[23]  Xing Xing,et al.  Event-Triggered Filtering for Nonlinear Networked Discrete-Time Systems , 2015, IEEE Transactions on Industrial Electronics.

[24]  Jian Sun,et al.  Event-Triggered Nonlinear Model Predictive Control with Bounded Disturbances and State-dependent Uncertainties , 2017 .

[25]  Huiping Li,et al.  Robust Receding Horizon Control for Networked and Distributed Nonlinear Systems , 2016 .

[26]  Demin Xu,et al.  Aperiodic Robust Model Predictive Control for Constrained Continuous-Time Nonlinear Systems: An Event-Triggered Approach , 2018, IEEE Transactions on Cybernetics.

[27]  Jun Wang,et al.  Tube-Based Robust Model Predictive Control of Nonlinear Systems via Collective Neurodynamic Optimization , 2016, IEEE Transactions on Industrial Electronics.

[28]  Yuanqing Xia,et al.  Event-Based Model Predictive Tracking Control of Nonholonomic Systems With Coupled Input Constraint and Bounded Disturbances , 2018, IEEE Transactions on Automatic Control.