https://orcid.org/0000-0003-2186-1187
Abstract
This paper centers on the finite-time control problem of the helicopter system in the midst of external disturbances, gain fluctuations, and actuator faults. Precisely, the finite-time boundedness and input–output finite-time stability are obtained concurrently to preclude huge undesirable values for both state and output, respectively, during specific transients. In particular, a particle swarm optimization setup is put forward for lowering the cost function and enhancing the overall reliability of the system. Furthermore, the fault-tolerant resilient control scheme is tailored to exhibit strong resistance to failures in the actuator and variations in the gain matrix. By blending the Lyapunov stability theory with the concept of finite time, we attain the essential requirements to ensure the stability of the closed-loop system over a finite span of time. Subsequently, the explicit methodology for obtaining the gain matrix is laid out pursuant to the established requirements. In particular, simulation results are presented to analyze the potential and significance of the devised control scheme.
Issue Section:
Research Papers
References
1.
Cai
, X.
, Shi
, K.
, She
, K.
, Park
, P.
, Zhong
, S.
, Kwon
, O.
, and Yu
, Y.
, 2023
, “Event-Triggered Control Strategy for 2-Dof Helicopter System Under Dos Attacks
,” IEEE Trans. Transp. Electrif.
, 9
(2
), pp. 3240
–3254
.10.1109/TTE.2022.32270862.
Zhang
, H.
, and Liu
, J.
, 2021
, “Event-Triggered Fuzzy Flight Control of a Two-Degree-of-Freedom Helicopter System
,” IEEE Trans. Fuzzy Syst.
, 29
(10
), pp. 2949
–2962
.10.1109/TFUZZ.2020.30097553.
Liu
, H.
, Lu
, G.
, and Zhong
, Y.
, 2013
, “Robust LQR Attitude Control of a 3-DoF Laboratory Helicopter for Aggressive Maneuvers
,” IEEE Trans. Ind. Electron.
, 60
(10
), pp. 4627
–4636
.10.1109/TIE.2012.22162334.
Zheng
, B.
, and Zhong
, Y.
, 2011
, “Robust Attitude Regulation of a 3-DoF Helicopter Benchmark: Theory and Experiments
,” IEEE Trans. Ind. Electron.
, 58
(2
), pp. 660
–670
.10.1109/TIE.2010.20465795.
Shen
, H.
, Hu
, X.
, Wang
, J.
, Cao
, J.
, and Qian
, W.
, 2023
, “Non-Fragile h Synchronization for Markov Jump Singularly Perturbed Coupled Neural Networks Subject to Double-Layer Switching Regulation
,” IEEE Trans. Neural Networks Learn. Syst.
, 34
(5
), pp. 2682
–2692
.10.1109/TNNLS.2021.31076076.
Shen
, H.
, Zhang
, Z.
, Li
, F.
, and Yan
, H.
, 2023
, “Non-Fragile H∞ Control for Piecewise-Homogeneous Hidden Semi-Markov Lur'e Systems
,” IEEE Trans. Circuits Syst. II: Express Briefs
, 71(1), pp. 306
–310
.10.1109/TCSII.2023.33000967.
Li
, X.
, She
, K.
, Shi
, K.
, Cheng
, J.
, Zhong
, S.
, and Peng
, Z.
, 2024
, “Nonfragile Switched Sampled-Data Control for Ship Electric Propulsion Systems With Stochastic Actuator Failures: A Dual-Sided Looped Fuzzy Lyapunov Functional
,” Fuzzy Sets Syst.
, 483
, p. 108914
.10.1016/j.fss.2024.1089148.
Azarang
, A.
, Miri
, M.
, Kamaei
, S.
, and Asemani
, M. H.
, 2018
, “Nonfragile Fuzzy Output Feedback Synchronization of a New Chaotic System: Design and Implementation
,” ASME J. Comput. Nonlinear Dyn.
, 13
(1
), p. 011008
.10.1115/1.40374169.
Kchaou
, M.
, Jerbi
, H.
, Toual
, B.
, and Kouzou
, A.
, 2022
, “Non-Fragile Mixed h/Passive-Based Asynchronous Sliding Mode Control for Nonlinear Singular Markovian Jump Systems
,” Int. J. Syst. Sci.
, 53
(3
), pp. 447
–467
.10.1080/00207721.2021.196191210.
Wang
, X.
, Shao
, Y.
, Zhang
, Z.
, Shen
, M.
, and Karimi
, H. R.
, 2023
, “Data-Driven Fault-Tolerant Control for Nonlinear Systems With Output Saturation
,” Chaos, Solitons Fractals
, 173
, p. 113626
.10.1016/j.chaos.2023.11362611.
Wu
, L.-B.
, Park
, J. H.
, Guo
, L.-D.
, and Huang
, S.-J.
, 2024
, “Prescribed Performance Event-Triggered Fault-Tolerant Control of Uncertain Pure-Feedback Nonlinear Systems
,” Int. J. Control
, 97
(7
), pp. 1532
–1541
.10.1080/00207179.2023.221424812.
Yu
, Y.
, Guo
, J.
, Chadli
, M.
, and Xiang
, Z.
, 2023
, “Distributed Adaptive Fuzzy Formation Control of Uncertain Multiple Unmanned Aerial Vehicles With Actuator Faults and Switching Topologies
,” IEEE Trans. Fuzzy Syst.
, 31
(3
), pp. 919
–929
.10.1109/TFUZZ.2022.319344013.
Satheesh
, T.
, Aravinth
, N.
, Sakthivel
, R.
, and Panneerselvam
, V.
, 2024
, “Fault Alarm-Based Hybrid Control for Interval Type-2 Fuzzy Cyber-Physical Systems
,” IEEE Trans. Circuits Syst. II: Express Briefs
, 71
(4
), pp. 2154
–2158
.10.1109/TCSII.2023.333508814.
Yao
, W.
, Su
, L.
, Wang
, Y.
, Wang
, J.
, and Shen
, H.
, 2024
, “Extended Dissipative Control for Interval Type-2 TS Fuzzy Markov Jump Systems Subject to Actuator Faults
,” Cybern. Syst.
, 55
(7
), pp. 1537
–1561
.10.1080/01969722.2022.213894215.
Jerbi
, H.
, Kchaou
, M.
, Alshammari
, O.
, Abassi
, R.
, and Popescu
, D.
, 2022
, “Observer-Based Feedback Control of Interval-Valued Fuzzy Singular System With Time-Varying Delay and Stochastic Faults
,” Int. J. Comput. Commun. Control
, 17
(6
), pp. 3894
–3904
.10.15837/ijccc.2022.6.495716.
Jiang
, T.
, Zhang
, Y.
, Park
, J. H.
, Cai
, X.
, and Shi
, K.
, 2023
, “Finite-Time Boundedness of Networked Control Systems Via Hybrid Predictive Control Based on Cloud Storage Method
,” Inf. Sci.
, 622
, pp. 1092
–1108
.10.1016/j.ins.2022.12.00617.
Cheng
, J.
, Park
, J. H.
, and Wu
, Z.-G.
, 2023
, “Finite-Time Control of Markov Jump Lur'e Systems With Singular Perturbations
,” IEEE Trans. Autom. Control
, 68
(11
), pp. 6804
–6811
.10.1109/TAC.2023.323829618.
Zhang
, C.
, Zong
, G.
, Su
, S. F.
, Qi
, W.
, and Chadli
, M.
, 2023
, “Finite-Time Event-Triggered Stabilization for Discrete-Time Fuzzy Markov Jump Singularly Perturbed Systems
,” IEEE Trans. Cybern.
, 53
(7
), pp. 4511
–4520
.10.1109/TCYB.2022.320743019.
Razmjooei
, H.
, and Shafiei
, M. H.
, 2020
, “Partial Finite-Time Stabilization of Perturbed Nonlinear Systems Based on the Novel Concept of Nonsingular Terminal Sliding Mode Method
,” ASME J. Comput. Nonlinear Dyn.
, 15
(2
), p. 021005
.10.1115/1.404563220.
Yan
, H.
, Tian
, Y.
, Li
, H.
, Zhang
, H.
, and Li
, Z.
, 2019
, “Input–Output Finite-Time Mean Square Stabilization of Nonlinear Semi-Markovian Jump Systems
,” Automatica
, 104
, pp. 82
–89
.10.1016/j.automatica.2019.02.02421.
Amato
, F.
, Carannante
, G.
, De Tommasi
, G.
, and Pironti
, A.
, 2012
, “Input–Output Finite-Time Stability of Linear Systems: Necessary and Sufficient Conditions
,” IEEE Trans. Autom. Control
, 57
(12
), pp. 3051
–3063
.10.1109/TAC.2012.219915122.
Qi
, W.
, Zong
, G.
, and Ki Ahn
, C.
, 2022
, “Input–Output Finite-Time Asynchronous Smc for Nonlinear Semi-Markov Switching Systems With Application
,” IEEE Trans. Syst., Man, Cybern.: Syst.
, 52
(8
), pp. 5344
–5353
.10.1109/TSMC.2021.312296523.
Guo
, Y.
, Yao
, Y.
, Wang
, S.
, Ma
, K.
, Liu
, K.
, and Guo
, J.
, 2014
, “Input–Output Finite-Time Stabilization of Linear Systems With Finite-Time Boundedness
,” ISA Trans.
, 53
(4
), pp. 977
–982
.10.1016/j.isatra.2014.05.01824.
Charfeddine
, S.
, Alharbi
, H.
, Jerbi
, H.
, Kchaou
, M.
, Abbassi
, R.
, and Leiva
, V.
, 2022
, “A Stochastic Optimization Algorithm to Enhance Controllers of Photovoltaic Systems
,” Mathematics
, 10
(12
), p. 2128
.10.3390/math1012212825.
Kennedy
, J.
, and Eberhart
, R.
, 1995
, “Particle Swarm Optimization
,” Proceedings of ICNN'95-International Conference on Neural Networks
, Perth, WA, Australia, Nov. 27–Dec. 1, pp. 1942
–1948
.10.1109/ICNN.1995.48896826.
Zhao
, B.
, Luo
, F.
, Lin
, H.
, and Liu
, D.
, 2021
, “Particle Swarm Optimized Neural Networks Based Local Tracking Control Scheme of Unknown Nonlinear Interconnected Systems
,” Neural Networks
, 134
, pp. 54
–63
.10.1016/j.neunet.2020.09.02027.
Yang
, Y.
, Niu
, Y.
, and Reza Karimi
, H.
, 2022
, “Dynamic Learning Control Design for Interval Type-2 Fuzzy Singularly Perturbed Systems: A Component-Based Event-Triggering Protocol
,” Int. J. Robust Nonlinear Control
, 32
(5
), pp. 2518
–2535
.10.1002/rnc.566128.
Wang
, J.
, Peng
, H.
, Tu
, M.
, Pérez‐Jiménez
, J. M.
, and Shi
, P.
, 2016
, “A Fault Diagnosis Method of Power Systems Based on an Improved Adaptive Fuzzy Spiking Neural p Systems and PSO Algorithms
,” Chin. J. Electron.
, 25
(2
), pp. 320
–327
.10.1049/cje.2016.03.01929.
Jiang
, M.
, Luo
, Y. P.
, and Yang
, S. Y.
, 2007
, “Stochastic Convergence Analysis and Parameter Selection of the Standard Particle Swarm Optimization Algorithm
,” Inf. Process. Lett.
, 102
(1
), pp. 8
–16
.10.1016/j.ipl.2006.10.00530.
Lin
, H.
, Zhao
, B.
, Liu
, D.
, and Alippi
, C.
, 2020
, “Data-Based Fault Tolerant Control for Affine Nonlinear Systems Through Particle Swarm Optimized Neural Networks
,” IEEE/CAA J. Autom. Sin.
, 7
(4
), pp. 954
–964
.10.1109/JAS.2020.100322531.
Estevez
, J.
, Lopez-Guede
, J. M.
, and Graña
, M.
, 2016
, “Particle Swarm Optimization Quadrotor Control for Cooperative Aerial Transportation of Deformable Linear Objects
,” Cybern. Syst.
, 47
(1–2
), pp. 4
–16
.10.1080/01969722.2016.1128759Copyright © 2025 by ASME
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