In this effort, we utilize a decentralized neuro-adaptive scheme in extinguishing both the chaotic and hyperchaotic dynamics of the so-called “Smart Valves” network. In particular, a network of two dynamically interconnected bidirectional solenoid actuated butterfly valves undergoes the harmful chaotic/hyperchaotic dynamics subject to some initial conditions and critical parameters. Crucial trade-offs, including robustness, computational burden, and practical feasibility of the control scheme, are thoroughly investigated. The advantages and shortcomings of the decentralized neuro-adaptive method are compared with those of the direct decentralized adaptive one to yield a computationally efficient, practically feasible, and robust scheme in the presence of the coupled harmful responses.
Issue Section:
Research Papers
References
1.
Naseradinmousavi
, P.
, Ashrafiuon
, H.
, and Ayoubi
, M. A.
, 2018
, “An Adaptive Centralized Approach to Control Chaotic and Hyperchaotic Dynamics of Smart Valves Network
,” ASME J. Comput. Nonlinear Dyn.
, 13
(1
), p. 011002
.2.
Naseradinmousavi
, P.
, Segala
, D. B.
, and Nataraj
, C.
, 2016
, “Chaotic and Hyperchaotic Dynamics of Smart Valves System Subject to a Sudden Contraction
,” ASME J. Comput. Nonlinear Dyn.
, 11
(5
), p. 051025
.3.
Naseradinmousavi
, P.
, Krstic
, M.
, and Nataraj
, C.
, 2016
, “Design Optimization of Dynamically Coupled Actuated Butterfly Valves Subject to a Sudden Contraction
,” ASME J. Mech. Des.
, 138
(4
), p. 041402
.4.
Naseradinmousavi
, P.
, Machiani
, S. G.
, Ayoubi
, M. A.
, and Nataraj
, C.
, 2017
, “Coupled Operational Optimization of Smart Valve System Subject to Different Approach Angles of a Pipe Contraction
,” J. Struct. Multidiscip. Optim.
, 55
(3
), pp. 1001
–1015
.5.
Naseradinmousavi
, P.
, 2014
, “A Novel Nonlinear Modeling and Dynamic Analysis of Solenoid Actuated Butterfly Valves Coupled in Series
,” ASME J. Dyn. Syst. Meas. Control
, 137
(1
), p. 014505
.6.
Naseradinmousavi
, P.
, and Nataraj
, C.
, 2013
, “Optimal Design of Solenoid Actuators Driving Butterfly Valves
,” ASME J. Mech. Des.
, 135
(9
), p. 094501
.7.
Naseradinmousavi
, P.
, and Nataraj
, C.
, 2012
, “Transient Chaos and Crisis Phenomena in Butterfly Valves Driven by Solenoid Actuators
,” J. Commun. Nonlinear Sci. Numer. Simul.
, 17
(11
), pp. 4336
–4345
.8.
Lee
, D.
, Naseradinmousavi
, P.
, and Nataraj
, C.
, 2012
, “Nonlinear Model-Based Adaptive Control of a Solenoid-Valve System
,” J. Control Sci. Eng.
, 2012
, p. 846458.9.
Naseradinmousavi
, P.
, and Nataraj
, C.
, 2011
, “Nonlinear Mathematical Modeling of Butterfly Valves Driven by Solenoid Actuators
,” J. Appl. Math. Model.
, 35
(5
), pp. 2324
–2335
.10.
Naseradinmousavi
, P.
, Ashrafiuon
, H.
, and Bagheri
, M.
, 2018
, “Suppressing Chaotic and Hyperchaotic Dynamics of Smart Valves Network Using a Centralized Adaptive Approach
,” American Control Conference
(ACC), Milwaukee, WI, June 27–29, Paper No. 1056.11.
Naseradinmousavi
, P.
, Bagheri
, M.
, Ashrafiuon
, H.
, Canova
, M.
, and Segala
, D. B.
, 2017
, “Suppressing Chaotic/Hyperchaotic Dynamics of Smart Valves Network Using Decentralized and Centralized Schemes
,” ASME
Paper No. DSCC2017-5006.12.
Naseradinmousavi
, P.
, Krstic
, M.
, Bagheri
, M.
, and Nataraj
, C.
, 2016
, “Coupled Chaotic and Hyperchaotic Dynamics of Actuated Butterfly Valves Operating in Series
,” ASME
Paper No. DSCC2016-9601.13.
Naseradinmousavi
, P.
, Bagheri
, M.
, and Nataraj
, C.
, 2016
, “Coupled Operational Optimization of Smart Valve System Subject to Different Approach Angles of a Pipe Contraction
,” ASME
Paper No. DSCC2016-9627.14.
Naseradinmousavi
, P.
, and Nataraj
, C.
, 2015
, “Design Optimization of Solenoid Actuated Butterfly Valves Dynamically Coupled in Series
,” ASME
Paper No. DSCC2015-9605.15.
Naseradinmousavi
, P.
, 2015
, “Optimal Design of Solenoid Actuated Butterfly Valves Dynamically Coupled in Series
,” ASME
Paper No. IMECE2015-50094.16.
Naseradinmousavi
, P.
, and Nataraj
, C.
, 2011
, “A Chaotic Blue Sky Catastrophe of Butterfly Valves Driven by Solenoid Actuators
,” ASME
Paper No. IMECE2011-62608.17.
Zhang
, X.
, and Liao
, L.
, 2016
, “Compound Synchronization Based on Memristive Cellular Neural Network of Chaos System
,” ASME J. Comput. Nonlinear Dyn.
, 12
(3
), p. 031002
.18.
Chang-Jian
, C.-W.
, 2014
, “Gear Dynamics Analysis With Turbulent Journal Bearings Mounted Hybrid Squeeze Film Damper-Chaos and Active Control Analysis
,” ASME J. Comput. Nonlinear Dyn.
, 10
(1
), p. 011011
.19.
Morel
, C.
, Vlad
, R.
, and Morel
, J.-Y.
, 2008
, “Anticontrol of Chaos Reduces Spectral Emissions
,” ASME J. Comput. Nonlinear Dyn.
, 3
(4
), p. 041009
.20.
Luo
, R.
, and Zeng
, Y.
, 2016
, “The Control and Synchronization of a Class of Chaotic Systems With Output Variable and External Disturbance
,” ASME J. Comput. Nonlinear Dyn.
, 11
(5
), p. 051011
.21.
Lin
, C.-H.
, 2015
, “Application of v-Belt Continuously Variable Transmission System Using Hybrid Recurrent Laguerre Orthogonal Polynomials Neural Network Control System and Modified Particle Swarm Optimization
,” ASME J. Comput. Nonlinear Dyn.
, 10
(5
), p. 051019
.22.
Reddy
, B. S.
, and Ghosal
, A.
, 2016
, “Asymptotic Stability and Chaotic Motions in Trajectory Following Feedback Controlled Robots
,” ASME J. Comput. Nonlinear Dyn.
, 11
(5
), p. 051012
.23.
Khamsuwan
, P.
, and Kuntanapreeda
, S.
, 2016
, “A Linear Matrix Inequality Approach to Output Feedback Control of Fractional-Order Unified Chaotic Systems With One Control Input
,” ASME J. Comput. Nonlinear Dyn.
, 11
(5
), p. 051021
.24.
Merat
, K.
, Chekan
, J. A.
, Salarieh
, H.
, and Alasty
, A.
, 2014
, “Control of Discrete Time Chaotic Systems Via Combination of Linear and Nonlinear Dynamic Programming
,” ASME J. Comput. Nonlinear Dyn.
, 10
(1
), p. 011008
.25.
Tian
, X.
, and Fei
, S.
, 2015
, “Adaptive Control for Fractional-Order Micro-Electro-Mechanical Resonator With Nonsymmetric Dead-Zone Input
,” ASME J. Comput. Nonlinear Dyn.
, 10
(6
), p. 061022
.26.
Arefi
, M. M.
, 2016
, “Adaptive Robust Stabilization of Rossler System With Time-Varying Mismatched Parameters Via Scalar Input
,” ASME J. Comput. Nonlinear Dyn.
, 11
(4
), p. 041024
.27.
Chen
, D.
, and Liu
, W.
, 2016
, “Chaotic Behavior and Its Control in a Fractional-Order Energy Demand-Supply System
,” ASME J. Comput. Nonlinear Dyn.
, 11
(6
), p. 061010
.28.
Chen
, X.
, Cao
, J.
, Qiu
, J.
, Alsaedi
, A.
, and Alsaadi
, F. E.
, 2016
, “Adaptive Control of Multiple Chaotic Systems With Unknown Parameters in Two Different Synchronization Modes
,” Advances in Difference Equations
, Springer, New York, p. 231
.29.
Zomaya
, A. Y.
, and Nabhan
, T. M.
, 1993
, “Centralized and Decentralized Neuro-Adaptive Robot Controllers
,” Neural Networks
, 6
(2
), pp. 223
–244
.30.
Chen
, Y. H.
, 1991
, “Decentralized Adaptive Robust Control Design: The Uncertainty is Time Varying
,” ASME J. Dyn. Syst. Meas. Control
, 113
(3
), pp. 515
–518
.31.
Hsiao
, F.-H.
, Liang
, Y.-W.
, Xu
, S.-D.
, and Lee
, G.-C.
, 2005
, “Decentralized Stabilization of Neural Network Linearly Interconnected Systems Via t-s Fuzzy Control
,” ASME J. Dyn. Syst. Meas. Control
, 129
(3
), pp. 343
–351
.32.
Karpenko
, M.
, Sepehri
, N.
, and Anderson
, J.
, 2007
, “Decentralized Coordinated Motion Control of Two Hydraulic Actuators Handling a Common Object
,” ASME J. Dyn. Syst. Meas. Control
, 129
(5
), pp. 729
–741
.33.
Yang
, Y.
, and Yue
, D.
, 2017
, “Observer-Based Decentralized Adaptive NNs Fault-Tolerant Control of a Class of Large-Scale Uncertain Nonlinear Systems With Actuator Failures
,” IEEE Trans. Syst., Man, Cybern. Syst.
, PP
(99
), pp. 1
–15
.34.
Eltantawie
, M. A.
, 2012
, “Decentralized Neuro-Fuzzy Control for Half Car With Semi-Active Suspension System
,” Int. J. Automot. Technol.
, 13
(3
), pp. 423
–431
.35.
Shi
, L.
, and Singh
, S. K.
, 1992
, “Decentralized Adaptive Controller Design for Large-Scale Systems With Higher-Order Interconnections
,” American Control Conference
(ACC
), Chicago, IL, June 24–26, pp. 3146
–3150
.36.
Duan
, N.
, and Min
, H.-F.
, 2016
, “Decentralized Adaptive NN State-Feedback Control for Large-Scale Stochastic High-Order Nonlinear Systems
,” J. Neurocomput.
, 173
, pp. 1412
–1421
.37.
Tong
, S.
, Li
, Y.
, and Wang
, T.
, 2013
, “Adaptive Fuzzy Decentralized Output Feedback Control for Stochastic Nonlinear Large-Scale Systems Using DSC Technique
,” Int. J. Robust Nonlinear Control
, 23
(4
), pp. 381
–399
.38.
Zhang
, X.
, Ma
, H.
, and Yang
, C.
, 2017
, “Decentralized Adaptive Control of a Class of Hidden Leader-Follower Nonlinearly Parameterized Coupled Multi-Agent Systems
,” IET Control Theory Appl.
, 11
(17
), pp. 3016
–3025
.39.
Skworcow
, P.
, Ulanicki
, B.
, AbdelMeguid
, H.
, and Paluszczyszyn
, D.
, 2010
, “Model Predictive Control for Energy and Leakage Management in Water Distribution Systems
,” UKACC Eighth International Conference on Control
, Coventry, UK, Sept. 7–10, pp. 990
–995
.40.
Negenborn
, R.
, Schutter
, B. D.
, and Hellendoorn
, J.
, 2008
, “Multi-Agent Model Predictive Control for Transportation Networks: Serial Vs. parallel Schemes
,” Eng. Appl. Artif. Intell.
, 21
(3
), pp. 353
–366
.41.
Bottura
, C. P.
, and Caceres
, A. F. T.
, 2002
, “Decentralized Control of Serial Interconnected Systems for River Water Quality Via Subspace Identification
,” American Control Conference
(ACC
), Anchorage, AK, May 8–10, pp. 3338
–3342
.42.
Joseph-Duran
, B.
, Ocampo-Martinez
, C.
, and Cembrano
, G.
, 2015
, “Output-Feedback Control of Combined Sewer Networks Through Receding Horizon Control With Moving Horizon Estimation
,” Water Resour. Res.
, 51
(10
), pp. 8129
–8145
.43.
Grosso
, J. M.
, Velarde
, P.
, Ocampo-Martinez
, C.
, Maestre
, J. M.
, and Puig
, V.
, 2016
, “Stochastic Model Predictive Control Approaches Applied to Drinking Water Networks
,” Optim. Control Appl. Methods
, 38
(4
), pp. 541
–588
.44.
Fambrini
, V.
, and Ocampo-Martinez
, C.
, 2009
, “Modelling and Decentralized Model Predictive Control of Drinking Water Networks,” Institut de Robotica i Informatica Industrial (CSIC-UPC), Barcelona, Spain, Technical Report No. IRI-TR-04-09
.45.
Barcelli
, D.
, Ocampo-Martinez
, C.
, Puig
, V.
, and Bemporad
, A.
, 2010
, “Decentralized Model Predictive Control of Drinking Water Networks Using an Automatic Subsystem Decomposition Approach
,” IFAC Proc. Vol.
, 43
(8), pp. 572–577.46.
Park
, J. Y.
, and Chung
, M. K.
, 2006
, “Study on Hydrodynamic Torque of a Butterfly Valve
,” ASME J. Fluids Eng.
, 128
(1
), pp. 190
–195
.47.
Naseradinmousavi
, P.
, 2012
, “Nonlinear Modeling, Dynamic Analysis, and Optimal Design and Operation of Electromechanical Valve Systems,” Ph.D. thesis
, Villanova University, Villanova, PA.48.
Bennett
, C. O.
, and Myers
, J. E.
, 1962
, Momentum, Heat, and Mass Transfer
, McGraw-Hill
, New York.49.
Massey
, B. S.
, and Ward-Smith
, J.
, 1998
, Mechanics of Fluids
, 7th ed., Taylor & Francis
, Boca Raton, FL.50.
Khalil
, H. K.
, 2002
, Nonlinear Systems
, Prentice Hall
, Upper Saddle River, NJ.51.
Wolf
, A.
, Swift
, J. B.
, Swinney
, H. L.
, and Vastano
, J. A.
, 1985
, “Determining Lyapunov Exponents From a Time Series
,” Phys. D
, 16
(3
), pp. 285
–317
.52.
Karimi
, B.
, Menhaj
, M. B.
, Karmi-Ghartemani
, M.
, and Saboori
, I.
, 2009
, “Decentralized Adaptie Control of Large-Scale Affine and Nonaffine Nonlinear Systems
,” IEEE Trans. Instrum. Meas.
, 58
(8
), pp. 2459
–2467
.53.
Spooner
, J. T.
, and Passino
, K. M.
, 1996
, “Adaptive Control of a Class of Decentralized Nonlinear Systems
,” IEEE Trans. Autom. Control
, 41
(2
), pp. 280
–284
.54.
Wen
, C.
, 1995
, “Indirect Robust Totally Decentralized Adaptive Control of Continuous-Time Interconnected Systems
,” IEEE Trans. Autom. Control
, 40
(6
), pp. 1122
–1126
.55.
Wen
, C.
, 1994
, “Direct Decentralized Adaptive Control of Interconnected Systems Having Arbitrary Subsystem Relative Degrees
,” 33rd IEEE Conference on Decision and Control
(CDC
), Lake Buena Vista, FL, Dec. 14–16, pp. 1187–1192.56.
Lang
, S.
, 1983
, Real Analysis
, Addison-Wesley
, Boston, MA.57.
Karimi
, B.
, Menhaj
, M. B.
, Karmi-Ghartemani
, M.
, and Saboori
, I.
, 2007
, “A Decentralized Direct Adaptive Controller for a Class of Large-Scale Interconnected Nonlinear Systems
,” IEEE International Symposium on Intelligent Signal Processing
(WISP
), Alcala de Henares, Spain, Oct. 3–5, pp. 265
–270
.58.
Karimi
, B.
, Menhaj
, M. B.
, and Saboori
, I.
, 2007
, “Decentralized Adaptive Control of Large-Scale Nonaffine Nonlinear Systems Using Radial Basis Function Neural Networks
,” IEICE Trans. Fundam.
, E90-A
(10
), pp. 2239
–2247
.59.
Krstić
, M.
, Kanellakopoulos
, I.
, and Kokotović
, P.
, 1995
, Nonlinear and Adaptive Control Design
, Wiley-Interscience
, New York.60.
Slotine
, J. J. E.
, and Li
, W.
, 1991
, Applied Nonlinear Control
, Prentice Hall
, Upper Saddle River, NJ.Copyright © 2018 by ASME
You do not currently have access to this content.
