Stabilizing Nonlinear Predictive Control over Nondeterministic Communication Networks

Author(s):  
R. Findeisen ◽  
P. Varutti
Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 4041
Author(s):  
Anca Maxim ◽  
Constantin-Florin Caruntu

Following the current technological development and informational advancement, more and more physical systems have become interconnected and linked via communication networks. The objective of this work is the development of a Coalitional Distributed Model Predictive Control (C- DMPC) strategy suitable for controlling cyber-physical, multi-agent systems. The motivation behind this endeavour is to design a novel algorithm with a flexible control architecture by combining the advantages of classical DMPC with Coalitional MPC. The simulation results were achieved using a test scenario composed of four dynamically coupled sub-systems, connected through an unidirectional communication topology. The obtained results illustrate that, when the feasibility of the local optimization problem is lost, forming a coalition between neighbouring agents solves this shortcoming and maintains the functionality of the entire system. These findings successfully prove the efficiency and performance of the proposed coalitional DMPC method.


ACS Omega ◽  
2021 ◽  
Author(s):  
Prajwal Shettigar J ◽  
Kshetrimayum Lochan ◽  
Gautham Jeppu ◽  
Srinivas Palanki ◽  
Thirunavukkarasu Indiran

Author(s):  
Marcelo M. Morato ◽  
Igor M.L. Pataro ◽  
Marcus V. Americano da Costa ◽  
Julio E. Normey-Rico

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Messaoud Bounkhel ◽  
Lotfi Tadj

We use nonlinear model predictive control to find the optimal harvesting effort of a renewable resource system with a nonlinear state equation that maximizes a nonlinear profit function. A solution approach is proposed and discussed and satisfactory numerical illustrations are provided.


2007 ◽  
Vol 40 (12) ◽  
pp. 216-221 ◽  
Author(s):  
Smaranda Cristea ◽  
César de Prada

2000 ◽  
Vol 33 (10) ◽  
pp. 701-706 ◽  
Author(s):  
Y. Wang ◽  
M. Ohshima ◽  
H. Seki ◽  
S. Ooyama ◽  
K. Akamatsu ◽  
...  

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