Regularized extreme learning machine–based intelligent adaptive control for uncertain nonlinear systems in networked control systems

2019 ◽  
Vol 23 (3-4) ◽  
pp. 617-625 ◽  
Author(s):  
Liang Chen ◽  
Jianyan Sun ◽  
Chunxiang Xu
Keyword(s):  
Adaptive Control ◽  
Nonlinear Systems ◽  
Control Systems ◽  
Extreme Learning Machine ◽  
Networked Control Systems ◽  
Networked Control ◽  
Uncertain Nonlinear Systems ◽  
Learning Machine

Adaptive Control for a Class of Uncertain Nonlinear Systems: Application to Photovoltaic Control Systems

2017 ◽  
Vol 62 (1) ◽  
pp. 393-398 ◽  
Author(s):  
Fernando Jaramillo-Lopez ◽  
Godpromesse Kenne ◽  
Francoise Lamnabhi-Lagarrigue
Keyword(s):  
Adaptive Control ◽  
Nonlinear Systems ◽  
Control Systems ◽  
Uncertain Nonlinear Systems

Optimal Bandwidth Allocation and QoS-Adaptive Control Co-Design for Networked Control Systems

2007 ◽  
Author(s):  
Kun Ji ◽  
Won-Jong Kim
Keyword(s):  
Adaptive Control ◽  
Control Systems ◽  
Bandwidth Allocation ◽  
Design Methodology ◽  
Networked Control Systems ◽  
Networked Control ◽  
Control Performance ◽  
Control Loop ◽  
Network Bandwidth

In this paper, we present a co-design methodology of dynamic optimal network-bandwidth allocation (ONBA) and adaptive control for networked control systems (NCSs) to optimize overall control performance and reduce total network-bandwidth usage. The proposed dynamic co-design strategy integrates adaptive feedback control with real-time scheduling. As part of this co-design methodology, a “closed-loop” ONBA algorithm for NCSs with communication constraints is presented. Network-bandwidth is dynamically assigned to each control loop according to the quality of performance (QoP) information of each control loop. As another part of the co-design methodology, a network quality of service (QoS)-adaptive control design approach is also presented. The idea is based on calculating new control values with reference to the network QoS parameters such as time delays and packet losses measured online. Simulation results show that this co-design approach significantly improves overall control performance and utilizes less bandwidth compared to static strategies.

Real-Time ${\cal L}_{1}$ Adaptive Control for Uncertain Networked Control Systems

2015 ◽  
Vol 60 (9) ◽  
pp. 2500-2505 ◽  
Author(s):  
Xiaofeng Wang ◽  
Evgeny Kharisov ◽  
Naira Hovakimyan
Keyword(s):  
Adaptive Control ◽  
Control Systems ◽  
Real Time ◽  
Networked Control Systems ◽  
Networked Control
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