Document Type : Research Articles

Authors

1 Center of advanced Control systems, Department of Electrical and Computer Engineering, Tarbiat Modares University, Tehran, Iran

2 control ,electrical engineering,tarbiat modares university,tehran,iran

Abstract

In this paper two linear constrained cooperative distributed extended dynamic matrix control (CDEDMC) and adaptive generalized predictive control (CDGPC) are proposed to control the uncertain nonlinear large-scale systems. In these approaches, a proposed cooperative optimization is employed which improves the global cost function. The cost values and convergence time are reduced using the proposed cooperative optimization strategy. The proposed approaches are designed based on the compensation of the mismatch between linearized and nominal nonlinear models. In CDEDMC the mismatch is considered as a disturbance and compensated; Also in CDGPC it is compensated using online identification of the linearized model. The typical distributed linear algorithms like DMC leads to an unstable response if the reference trajectory is a little far from the equilibrium point. This problem will be partially solved using the CDEDMC and will be completely solved using the CDGPC even if the reference trajectory is too far from the equilibrium point. The performance and effectiveness of proposed approaches are demonstrated through simulation of a typical uncertain nonlinear large-scale system.

Keywords

Main Subjects

[1] P. D. Christofides, R. Scattolini, D. M. De la Pena, and J.
Liu, “Distributed model predictive control: A tutorial

review and future research directions”
Journal of
Computers and Chemical Engineering
, Vol. 51, pp. 21-41,
Apr.
2013.

[2] A. Grancharova, T. A. Johansen, and S. Olaru,
“Dual-Mode distributed model predictive control of a
quadruple-tank system” Journal of Chemical Technology
and Metallurgy, Vol. 53, No. 4, pp. 674-682, May. 2018.

[3] N. Sadati, M. Rahmani, and M. Saif, “Two-Level Robust
Optimal Control of Large-Scale Nonlinear Systems”
IEEE
Systems Journal
, Vol. 9, No. 1, pp. 242-251, Mar. 2015.

[4] I. Stoyanova, E. Gumrukcu, G. Aragon, D. I.
Hidalgo-Rodriguez, A. Monti, and J. Myrzik, “Distributed
model predictive control strategies for coordination of
electro-thermal devices in a cooperative energy
management concept” Optimal Control Applications and
Methods, Vol. 41, pp. 170189, Aug. 2019.

[5] Y. Zou, X. Su, S. Li, Y. Niu, and D. Li, “Event-triggered
distributed predictive control for asynchronous
coordination of multi-agent systems” Automatica, Vol. 99,
pp. 9298, Jan. 2019.

[6] W. Jiao, Q. Wu, S. Huang, and J. Chen, “Decentralized
voltage control of wind farm based on gradient projection
method”
International Journal of Electrical Power &
Energy Systems
, Vol. 123, pp. 1-8, Dec. 2020.

[7] Y. Gao, L. Dai, Y. Xia, and Y. Liu, “Distributed model
predictive control for consensus of nonlinear second-order
multi-agent systems” International Journal of Robust and
Nonlinear Control, Vol. 27, pp. 830-842, Jul. 2016.

[8] X. Liu, Y. Shi, and D. Constantinescu, “Distributed model
predictive control of constrained weakly coupled nonlinear
systems” Systems & Control Letters, Vol. 74, pp. 41-49,
Dec. 2014.

[9] S. Rahmati, and H. Eliasi, “Robust Decentralized Model
Predictive Control for a Class of Interconnected systems”
International Journal of Industrial Electronics, Control
and Optimization, Vol. 3, No. 3, pp. 327-336, Jul. 2020.

[10] M. H. Yamchi, and R. M. Esfanjani, “Distributed
predictive formation control of networked mobile robots
subject to communication delay”
Robotics and
Autonomous Systems
, Vol. 91, pp. 194-207, May. 2017.

[11] X. Liu, Y. Shi, and D. Constantinescu, “Robust
Distributed Model Predictive Control of Constrained
Continuous-Time Nonlinear Systems Using Two-Layer
Invariant Sets” Journal of Dynamic Systems, Measurement,
and Control, Vol. 138, pp.1-7, Jun. 2016.

[12] Y. Zheng, S. Eben Li, K. Li, F. Borrelli, and J. Karl
Hedrick, “Distributed Model Predictive Control for
Heterogeneous Vehicle Platoons under Unidirectional
Topologies”
IEEE Transactions on Control Systems
Technology
, Vol. 25, No. 3, pp. 899-910, May. 2017.

[13] X. Yang, L. Zhang, W. Xie, and J. Zhang, “Sequential and
Iterative Distributed Model Predictive Control of
Multi-Motor Driving Cutterhead System for TBM”
IEEE
Access
, Vol. 7, pp. 46977-46989, Apr. 2019.

[14] S. Iles, J. Matusko, and F. Kolonic, “Sequential distributed
predictive control of a 3D tower crane” Control
Engineering Practice, Vol. 79, pp. 22-35, Oct. 2018.

[15] Y. Long, S. Liu, L. Xie, and K. H. Johansson, “Distributed
nonlinear model predictive control based on contraction
theory” International Journal of Robust and Nonlinear
Control, Vol. 28, pp. 112, Jul. 2017.

[16] X. Liu, Y. Shi, and D. Constantinescu, “Robust distributed
model predictive control of constrained dynamically
decoupled nonlinear systems: A contraction theory
perspective” Systems & Control Letters, Vol. 105, pp.
84-91, Jul. 2017.

[17] N. R. Esfahani and K. Khorasani, “A Distributed Model
Predictive Control (MPC) Fault Reconfiguration Strategy
for Formation Flying Satellites” International Journal of
Control, Vol. 89, No. 5, pp. 960-983, Nov. 2015.

[18] X. Kong, X. Liu, L. Ma, and K. Y. Lee, “Hierarchical
Distributed Model Predictive Control of Standalone
Wind/Solar/Battery Power System” IEEE Transactions on
Systems, Man, and Cybernetics: Systems, Vol. 49,
No. 8,
pp. 1570-1581, Aug. 2019.
[19] A. Mirzaei, and A. Ramezani, “Cooperative Distributed
Constrained Adaptive Generalized Predictive Control for
Uncertain Nonlinear Large-Scale Systems: Application to
Quadruple-Tank System” Journal of Electrical and
Computer Engineering Innovations, Vol. 7, No. 2, pp.
183-194, Jul. 2020.

[20] M. Ehsani, M. Saeidi, H. Radmanesh, and A. Abrishamifar,
“Comparisons between Generalized Predictive Control and
Linear Controllers in Multi-Input DC-DC Boost Converter”
International Journal of Industrial Electronics, Control
and Optimization, Vol. 1, No. 3, pp. 27-34, Jan. 2020.

[21] X. Xing, L. Xie, and H. Meng, “Cooperative energy
management optimization based on distributed MPC in
grid-connected microgrids community” Electrical Power
and Energy Systems, Vol. 107, pp. 186199, May. 2019.

[22] E. F. Camacho, and C. Bordons, “Model Predictive
Control”, Springer, Second Edition, Jul. 2007.

[23] E. Zakeri, S. A. Moezi, and M. Eghtesad, “Optimal
interval type-2 fuzzy fractional order super twisting
algorithm: A second order sliding mode controller for
fully-actuated and under-actuated nonlinear systems” ISA
Transactions, Vol. 85, pp. 13-32, Feb. 2019.

[24] E. Zakeri, and H. Moeinkhah, “Digital control design for
an IPMC actuator using adaptive optimal proportional
integral plus method: Simulation and experimental study”
Sensors and Actuators A: Physical,
Vol. 298, pp. 1-14, Oct.
2019.