Networked multirobot systems under the coordinated control can perform tasks more effectively than a group of individually operating robots. This paper studies the group regional consensus of networked multirobot systems (formulated by second-order Lagrangian dynamics) having input disturbances under directed acyclic topology. An adaptive control protocol is designed to achieve group regional consensus of the networked Lagrangian systems with parametric uncertainties for both leader and leaderless cases. Sufficient conditions are established to guarantee group regional consensus for any prior given desired consensus errors. Compared with the existing work, a distinctive feature of the proposed control algorithm is that the stability analysis indicates the global validity of the obtained consensus results. Numerical examples are provided to demonstrate the effectiveness of the proposed scheme.
Skip Nav Destination
Article navigation
September 2017
Technical Briefs
Group Regional Consensus of Networked Lagrangian Systems With Input Disturbances
Jun Liu,
Jun Liu
Shanghai Institute of Applied Mathematics and Mechanics,
Shanghai University,
Shanghai 200072, China;
Shanghai University,
Shanghai 200072, China;
Department of Mathematics,
Jining University,
Qufu 273155, Shandong, China
Jining University,
Qufu 273155, Shandong, China
Search for other works by this author on:
Zhonghua Miao,
Zhonghua Miao
School of Mechatronic Engineering and Automation,
Shanghai University,
Shanghai 200072, China
Shanghai University,
Shanghai 200072, China
Search for other works by this author on:
Jinchen Ji,
Jinchen Ji
Faculty of Engineering and IT,
University of Technology Sydney,
PO Box 123, Broadway,
Ultimo 2007, NSW, Australia
University of Technology Sydney,
PO Box 123, Broadway,
Ultimo 2007, NSW, Australia
Search for other works by this author on:
Jin Zhou
Jin Zhou
Shanghai Institute of Applied Mathematics and Mechanics,
Shanghai Key Laboratory of
Mechanics in Energy Engineering,
Shanghai University,
Shanghai 200072, China
e-mail: jzhou@shu.edu.cn
Shanghai Key Laboratory of
Mechanics in Energy Engineering,
Shanghai University,
Shanghai 200072, China
e-mail: jzhou@shu.edu.cn
Search for other works by this author on:
Jun Liu
Shanghai Institute of Applied Mathematics and Mechanics,
Shanghai University,
Shanghai 200072, China;
Shanghai University,
Shanghai 200072, China;
Department of Mathematics,
Jining University,
Qufu 273155, Shandong, China
Jining University,
Qufu 273155, Shandong, China
Zhonghua Miao
School of Mechatronic Engineering and Automation,
Shanghai University,
Shanghai 200072, China
Shanghai University,
Shanghai 200072, China
Jinchen Ji
Faculty of Engineering and IT,
University of Technology Sydney,
PO Box 123, Broadway,
Ultimo 2007, NSW, Australia
University of Technology Sydney,
PO Box 123, Broadway,
Ultimo 2007, NSW, Australia
Jin Zhou
Shanghai Institute of Applied Mathematics and Mechanics,
Shanghai Key Laboratory of
Mechanics in Energy Engineering,
Shanghai University,
Shanghai 200072, China
e-mail: jzhou@shu.edu.cn
Shanghai Key Laboratory of
Mechanics in Energy Engineering,
Shanghai University,
Shanghai 200072, China
e-mail: jzhou@shu.edu.cn
1Corresponding author.
Contributed by the Dynamic Systems Division of ASME for publication in the JOURNAL OF DYNAMIC SYSTEMS, MEASUREMENT, AND CONTROL. Manuscript received March 15, 2016; final manuscript received January 18, 2017; published online June 5, 2017. Assoc. Editor: Dejan Milutinovic.
J. Dyn. Sys., Meas., Control. Sep 2017, 139(9): 094501 (6 pages)
Published Online: June 5, 2017
Article history
Received:
March 15, 2016
Revised:
January 18, 2017
Citation
Liu, J., Miao, Z., Ji, J., and Zhou, J. (June 5, 2017). "Group Regional Consensus of Networked Lagrangian Systems With Input Disturbances." ASME. J. Dyn. Sys., Meas., Control. September 2017; 139(9): 094501. https://doi.org/10.1115/1.4036029
Download citation file:
Get Email Alerts
Cited By
An Adaptive Sliding-Mode Observer-Based Fuzzy PI Control Method for Temperature Control of Laser Soldering Process
J. Dyn. Sys., Meas., Control
Fault detection of automotive engine system based on Canonical Variate Analysis combined with Bhattacharyya Distance
J. Dyn. Sys., Meas., Control
Multi Combustor Turbine Engine Acceleration Process Control Law Design
J. Dyn. Sys., Meas., Control (July 2025)
Related Articles
Nonlinear Robust Output Stabilization for Mechanical Systems Based on Luenberger-Like Controller/Observer
J. Dyn. Sys., Meas., Control (August,2017)
Robust Adaptive Compensation for a Class of Nonlinear Systems
J. Dyn. Sys., Meas., Control (March,2002)
Desired Compensation Adaptive Robust Control
J. Dyn. Sys., Meas., Control (November,2009)
Switching Control With Learning for a Class of Systems
J. Dyn. Sys., Meas., Control (September,2003)
Related Proceedings Papers
Related Chapters
Fault-Tolerant Control of Sensors and Actuators Applied to Wind Energy Systems
Electrical and Mechanical Fault Diagnosis in Wind Energy Conversion Systems
Dynamic Behavior in a Singular Delayed Bioeconomic Model
International Conference on Instrumentation, Measurement, Circuits and Systems (ICIMCS 2011)
Adaptive Control and Stability Analysis of Genetic Networks with SUM Regulation
Intelligent Engineering Systems through Artificial Neural Networks, Volume 16