Distributed consensus tracking control of nonlinear multi-agent systems with dynamic output constraints and input saturation
This paper studies the distributed output-feedback consensus tracking problem for nonlinear multi-agent systems (MASs) subject to dynamic output constraints and input saturation. Firstly, a neural-network (NN) based high gain observer is designed to provide estimation for unmeasured state of each ag...
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| Published in | Journal of the Franklin Institute Vol. 360; no. 1; pp. 356 - 379 |
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| Main Authors | , , , , |
| Format | Journal Article |
| Language | English |
| Published |
Elsevier Ltd
01.01.2023
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| Online Access | Get full text |
| ISSN | 0016-0032 1879-2693 |
| DOI | 10.1016/j.jfranklin.2022.11.009 |
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| Abstract | This paper studies the distributed output-feedback consensus tracking problem for nonlinear multi-agent systems (MASs) subject to dynamic output constraints and input saturation. Firstly, a neural-network (NN) based high gain observer is designed to provide estimation for unmeasured state of each agent. To address the dynamic output constraints problem, a unified barrier function is proposed to convert the constrained system into unconstrained one. Then, command filter-based backstepping is applied in design procedures to construct the distributed consensus tracking protocol and adaptive law. The auxiliary systems are constructed to generate additional error signals which are used to reduce the influence of input saturation. Thirdly, the boundedness of all signals in closed-loop MASs is proved based on Lyapunov stability theory. The consensus tracking error converges to an arbitrarily small neighborhood around the origin and the general dynamic output constraints are not violated under saturated input. Finally, The effectiveness of the proposed control protocol is verified using a simulation example. |
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| AbstractList | This paper studies the distributed output-feedback consensus tracking problem for nonlinear multi-agent systems (MASs) subject to dynamic output constraints and input saturation. Firstly, a neural-network (NN) based high gain observer is designed to provide estimation for unmeasured state of each agent. To address the dynamic output constraints problem, a unified barrier function is proposed to convert the constrained system into unconstrained one. Then, command filter-based backstepping is applied in design procedures to construct the distributed consensus tracking protocol and adaptive law. The auxiliary systems are constructed to generate additional error signals which are used to reduce the influence of input saturation. Thirdly, the boundedness of all signals in closed-loop MASs is proved based on Lyapunov stability theory. The consensus tracking error converges to an arbitrarily small neighborhood around the origin and the general dynamic output constraints are not violated under saturated input. Finally, The effectiveness of the proposed control protocol is verified using a simulation example. |
| Author | Tang, Xiangyu Dong, Xiwang Li, Qingdong Yu, Jianglong Ren, Zhang |
| Author_xml | – sequence: 1 givenname: Xiangyu surname: Tang fullname: Tang, Xiangyu organization: School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, China – sequence: 2 givenname: Jianglong surname: Yu fullname: Yu, Jianglong email: sdjxyjl@buaa.edu.cn organization: School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, China – sequence: 3 givenname: Xiwang surname: Dong fullname: Dong, Xiwang organization: School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, China – sequence: 4 givenname: Qingdong surname: Li fullname: Li, Qingdong organization: School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, China – sequence: 5 givenname: Zhang surname: Ren fullname: Ren, Zhang organization: School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, China |
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| Cites_doi | 10.1016/j.automatica.2020.109161 10.1109/TFUZZ.2021.3130201 10.1016/j.automatica.2008.11.017 10.1016/j.automatica.2020.109181 10.1109/TAC.2020.2981084 10.1109/TAC.2008.919848 10.1002/asjc.1104 10.1016/j.automatica.2016.11.019 10.2514/1.62110 10.1016/j.jfranklin.2019.07.021 10.1109/TCYB.2015.2394797 10.1016/j.neucom.2021.05.079 10.1109/TCST.2017.2757448 10.1016/j.neucom.2014.11.041 10.1016/j.automatica.2016.01.027 10.1002/rnc.5004 10.1109/TCYB.2018.2879892 10.1109/TAC.2018.2874877 10.1016/j.jfranklin.2019.12.015 10.1109/TSMC.2019.2956063 10.1109/TCST.2017.2728518 10.1002/rnc.4119 10.1049/iet-cta.2015.0627 10.1016/j.automatica.2017.03.033 10.1016/j.jfranklin.2020.07.037 10.1109/TCST.2014.2314460 10.1016/j.automatica.2018.07.030 10.1016/j.automatica.2020.109102 10.1109/TNNLS.2018.2803827 10.1016/j.isatra.2020.07.030 10.1109/TIE.2016.2636810 10.1016/j.isatra.2018.07.039 10.1109/9.486648 10.1080/00207179.2015.1088967 10.1016/j.automatica.2016.06.025 10.1016/j.neucom.2017.12.052 10.1016/j.ins.2018.11.038 10.1016/j.jfranklin.2018.07.033 10.1109/TAC.2018.2810514 10.1109/TCYB.2015.2411285 10.1016/j.automatica.2019.02.019 10.1016/j.jfranklin.2020.04.028 |
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| References | Wang, Wang, Peng, Wang (bib0036) 2016; 18 Zhao, Yu, Lin (bib0037) 2018; 80 Acosta, Dòria-Cerezo, Fossas (bib0030) 2018; 28 Zhang, Xia, Yi (bib0020) 2017; 81 Yang, Xiao, Yin, Zhou, Lu (bib0044) 2020; 30 Li (bib0021) 2020; 121 Zhu, Du, Kao (bib0043) 2018; 355 Chowdhury, Khalil (bib0004) 2021; 66 Zhang, Dong, Han, Li, Ren (bib0005) 2021 Zhao, Yu, Lin (bib0038) 2019; 478 Li, Li (bib0013) 2015; 153 Zheng, Huang, Xie, Zhu (bib0011) 2018; 26 Liu, Hou, Ni, Li, Wu (bib0026) 2020; 357 Gao, Huang, Shi, Zhu (bib0032) 2020; 357 Zhang, Dong, Ouyang, Yin, Peng (bib0025) 2018; 29 Zhao, Song, Chen, Chen (bib0031) 2020; 119 Yoo, Park (bib0012) 2019; 103 Meng, Yang, Si, Sun (bib0019) 2016; 46 Tohidi, Yildiz, Kolmanovsky (bib0015) 2020; 121 Shen, Xu (bib0028) 2018; 97 Pan, Li, Liang, Lam (bib0007) 2022; 30 Shi, Xu, Liu, Zhang (bib0010) 2020; 50 Liu, Wang, Xu (bib0033) 2020; 357 Hua, You, Guan (bib0009) 2016; 73 Sun, Su, Liu, Sun (bib0024) 2021; 51 Qin, Ma, Shi, Wang (bib0001) 2017; 64 ur Rehman, Rehan, Riaz, Abid, Iqbal (bib0040) 2020; 107 Ma, Zong, Zhao, Huo (bib0041) 2020; 357 Wang, Wen, Huang (bib0008) 2017; 77 Liu, Lu (bib0017) 2014; 37 Polycarpou (bib0042) 1996; 41 Yin, Yue, Hu (bib0039) 2016; 89 Zhao, Lin (bib0034) 2016; 68 Li, Yan, Shi (bib0014) 2018; 63 Cui, Xu, Lewis, Zhang, Ma (bib0035) 2016; 10 Tee, Ge, Tay (bib0018) 2009; 45 Pan, Wu, Lam (bib0006) 2022 He, Chen, Yin (bib0022) 2016; 46 Nair, Behera, Kumar (bib0003) 2019; 27 Guo, Xue, Pan (bib0029) 2021; 458 Dong, Yu, Shi, Zhong (bib0002) 2015; 23 Azhmyakov, Raisch (bib0016) 2008; 53 Yu, Wang, Jo (bib0027) 2018; 295 Jin (bib0023) 2019; 64 Ma (10.1016/j.jfranklin.2022.11.009_bib0041) 2020; 357 Tee (10.1016/j.jfranklin.2022.11.009_bib0018) 2009; 45 Li (10.1016/j.jfranklin.2022.11.009_bib0013) 2015; 153 Azhmyakov (10.1016/j.jfranklin.2022.11.009_bib0016) 2008; 53 Shen (10.1016/j.jfranklin.2022.11.009_bib0028) 2018; 97 Dong (10.1016/j.jfranklin.2022.11.009_bib0002) 2015; 23 Liu (10.1016/j.jfranklin.2022.11.009_bib0033) 2020; 357 Wang (10.1016/j.jfranklin.2022.11.009_bib0036) 2016; 18 Zhao (10.1016/j.jfranklin.2022.11.009_bib0037) 2018; 80 Cui (10.1016/j.jfranklin.2022.11.009_bib0035) 2016; 10 Zhao (10.1016/j.jfranklin.2022.11.009_bib0038) 2019; 478 Gao (10.1016/j.jfranklin.2022.11.009_bib0032) 2020; 357 He (10.1016/j.jfranklin.2022.11.009_bib0022) 2016; 46 Zhang (10.1016/j.jfranklin.2022.11.009_bib0025) 2018; 29 Liu (10.1016/j.jfranklin.2022.11.009_bib0017) 2014; 37 Polycarpou (10.1016/j.jfranklin.2022.11.009_bib0042) 1996; 41 Chowdhury (10.1016/j.jfranklin.2022.11.009_bib0004) 2021; 66 Zhu (10.1016/j.jfranklin.2022.11.009_bib0043) 2018; 355 Zhang (10.1016/j.jfranklin.2022.11.009_bib0005) 2021 Guo (10.1016/j.jfranklin.2022.11.009_bib0029) 2021; 458 Zheng (10.1016/j.jfranklin.2022.11.009_bib0011) 2018; 26 Zhao (10.1016/j.jfranklin.2022.11.009_bib0034) 2016; 68 Meng (10.1016/j.jfranklin.2022.11.009_bib0019) 2016; 46 Shi (10.1016/j.jfranklin.2022.11.009_bib0010) 2020; 50 Acosta (10.1016/j.jfranklin.2022.11.009_bib0030) 2018; 28 Nair (10.1016/j.jfranklin.2022.11.009_bib0003) 2019; 27 Zhao (10.1016/j.jfranklin.2022.11.009_bib0031) 2020; 119 Qin (10.1016/j.jfranklin.2022.11.009_bib0001) 2017; 64 Tohidi (10.1016/j.jfranklin.2022.11.009_bib0015) 2020; 121 Pan (10.1016/j.jfranklin.2022.11.009_bib0006) 2022 Pan (10.1016/j.jfranklin.2022.11.009_bib0007) 2022; 30 Li (10.1016/j.jfranklin.2022.11.009_bib0021) 2020; 121 Jin (10.1016/j.jfranklin.2022.11.009_bib0023) 2019; 64 Wang (10.1016/j.jfranklin.2022.11.009_bib0008) 2017; 77 Yu (10.1016/j.jfranklin.2022.11.009_bib0027) 2018; 295 Yoo (10.1016/j.jfranklin.2022.11.009_bib0012) 2019; 103 Li (10.1016/j.jfranklin.2022.11.009_bib0014) 2018; 63 Yang (10.1016/j.jfranklin.2022.11.009_bib0044) 2020; 30 Liu (10.1016/j.jfranklin.2022.11.009_bib0026) 2020; 357 Hua (10.1016/j.jfranklin.2022.11.009_bib0009) 2016; 73 Yin (10.1016/j.jfranklin.2022.11.009_bib0039) 2016; 89 ur Rehman (10.1016/j.jfranklin.2022.11.009_bib0040) 2020; 107 Sun (10.1016/j.jfranklin.2022.11.009_bib0024) 2021; 51 Zhang (10.1016/j.jfranklin.2022.11.009_bib0020) 2017; 81 |
| References_xml | – volume: 46 start-page: 620 year: 2016 end-page: 629 ident: bib0022 article-title: Adaptive neural network control of an uncertain robot with full-state constraints publication-title: IEEE Trans. Cybern. – volume: 357 start-page: 6653 year: 2020 end-page: 6670 ident: bib0032 article-title: Nonlinear mapping-based fixed-time stabilization of uncertain nonholonomic systems with time-varying state constraints publication-title: J. Frankl. Inst. – volume: 64 start-page: 4972 year: 2017 end-page: 4983 ident: bib0001 article-title: Recent advances in consensus of multi-agent systems: a brief survey publication-title: IEEE Trans. Ind. Electron. – volume: 458 start-page: 24 year: 2021 end-page: 32 ident: bib0029 article-title: Neural networks-based adaptive tracking control of multi-agent systems with output-constrained and unknown hysteresis publication-title: Neurocomputing – volume: 41 start-page: 447 year: 1996 end-page: 451 ident: bib0042 article-title: Stable adaptive neural control scheme for nonlinear systems publication-title: IEEE Trans. Autom. Control – volume: 63 start-page: 4008 year: 2018 end-page: 4015 ident: bib0014 article-title: Triggering and control codesign in self-triggered modelpredictive control of constrained systems: with guaranteed performance publication-title: IEEE Trans. Autom. Control – volume: 30 start-page: 4764 year: 2020 end-page: 4778 ident: bib0044 article-title: Adaptive neural control for multiagent systems with asymmetric time-varying state constraints and input saturation publication-title: Int. J. Robust Nonlinear Control – volume: 23 start-page: 340 year: 2015 end-page: 348 ident: bib0002 article-title: Time-varying formation control for unmanned aerial vehicles: theories and applications publication-title: IEEE Trans. Control Syst. Technol. – volume: 121 start-page: 109161 year: 2020 ident: bib0015 article-title: Adaptive control allocation for constrained systems publication-title: Automatica – volume: 80 start-page: 187 year: 2018 end-page: 194 ident: bib0037 article-title: Command filter based adaptive fuzzy bipartite output consensus tracking of nonlinear coopetition multi-agent systems with input saturation publication-title: ISA Trans. – volume: 50 start-page: 1530 year: 2020 end-page: 1540 ident: bib0010 article-title: Global fixed-time consensus tracking of nonlinear uncertain multiagent systems with high-order dynamics publication-title: IEEE Trans. Cybern. – volume: 357 start-page: 1090 year: 2020 end-page: 1117 ident: bib0033 article-title: Distributed adaptive output consensus tracking for high-order nonlinear time-varying multi-agent systems with output constraints and actuator faults publication-title: J. Frankl. Inst. – volume: 107 start-page: 194 year: 2020 end-page: 205 ident: bib0040 article-title: Consensus tracking of nonlinear multi-agent systems under input saturation with applications: a sector-based approach publication-title: ISA Trans. – volume: 89 start-page: 653 year: 2016 end-page: 667 ident: bib0039 article-title: Adaptive periodic event-triggered consensus for multi-agent systems subject to input saturation publication-title: Int. J. Control – volume: 478 start-page: 355 year: 2019 end-page: 374 ident: bib0038 article-title: Distributed adaptive output consensus tracking of nonlinear multi-agent systems via state observer and command filtered backstepping publication-title: Inf. Sci. – volume: 51 start-page: 5577 year: 2021 end-page: 5586 ident: bib0024 article-title: Adaptive intelligent control for input and output constrained high-order uncertain nonlinear systems publication-title: IEEE Trans. Syst., Man, Cybern. – volume: 10 start-page: 509 year: 2016 end-page: 516 ident: bib0035 article-title: Distributed consensus tracking for non-linear multi-agent systems with input saturation: a command filtered backstepping approach publication-title: IET Control Theory Appl. – volume: 66 start-page: 184 year: 2021 end-page: 198 ident: bib0004 article-title: Practical synchronization in networks of nonlinear heterogeneous agents with application to power systems publication-title: IEEE Trans. Autom. Control – volume: 81 start-page: 232 year: 2017 end-page: 239 ident: bib0020 article-title: Adaptive neural dynamic surface control of strict-feedback nonlinear systems with full state constraints and unmodeled dynamics publication-title: Automatica – volume: 121 start-page: 109181 year: 2020 ident: bib0021 article-title: Barrier Lyapunov function-based adaptive asymptotic tracking of nonlinear systems with unknown virtual control coefficients publication-title: Automatica – volume: 295 start-page: 1 year: 2018 end-page: 7 ident: bib0027 article-title: Adaptive consensus control of output-constrained second-order nonlinear systems via neurodynamic optimization publication-title: Neurocomputing – volume: 27 start-page: 39 year: 2019 end-page: 47 ident: bib0003 article-title: Event-triggered finite-time integral sliding mode controller for consensus-based formation of multirobot systems with disturbances publication-title: IEEE Trans. Control Syst. Technol. – volume: 77 start-page: 133 year: 2017 end-page: 142 ident: bib0008 article-title: Distributed adaptive asymptotically consensus tracking control of nonlinear multi-agent systems with unknown parameters and uncertain disturbances publication-title: Automatica – volume: 26 start-page: 1851 year: 2018 end-page: 1859 ident: bib0011 article-title: Adaptive trajectory tracking control of a fully actuated surface vessel with asymmetrically constrained input and output publication-title: IEEE Trans. Control Syst. Technol. – start-page: 1 year: 2022 ident: bib0006 article-title: Security-based fuzzy control for nonlinear networked control systems with dos attacks via a resilient event-triggered scheme publication-title: IEEE Trans. Fuzzy Syst. – volume: 53 start-page: 993 year: 2008 end-page: 998 ident: bib0016 article-title: Convex control systems and convex optimal control problems with constraints publication-title: IEEE Trans. Autom. Control – volume: 68 start-page: 294 year: 2016 end-page: 304 ident: bib0034 article-title: Global leader-following consensus of a group of general linear systems using bounded controls publication-title: Automatica – volume: 46 start-page: 85 year: 2016 end-page: 95 ident: bib0019 article-title: Adaptive neural control of a class of output-constrained nonaffine systems publication-title: IEEE Trans. Cybern. – volume: 18 start-page: 619 year: 2016 end-page: 630 ident: bib0036 article-title: Cooperative adaptive fuzzy output feedback control for synchronization of nonlinear multi-agent systems in the presence of input saturation publication-title: Asian J. Control – year: 2021 ident: bib0005 article-title: Sensor network based distributed state estimation for maneuvering target with guaranteed performances publication-title: Neurocomputing – volume: 37 start-page: 750 year: 2014 end-page: 765 ident: bib0017 article-title: Solving nonconvex optimal control problems by convex optimization publication-title: J. Guid., Control, Dyn. – volume: 357 start-page: 9709 year: 2020 end-page: 9732 ident: bib0026 article-title: Asymmetric integral barrier Lyapunov function-based adaptive tracking control considering full-state with input magnitude and rate constraint publication-title: J. Frankl. Inst. – volume: 97 start-page: 64 year: 2018 end-page: 72 ident: bib0028 article-title: Distributed learning consensus for heterogenous high-order nonlinear multi-agent systems with output constraints publication-title: Automatica – volume: 355 start-page: 7548 year: 2018 end-page: 7569 ident: bib0043 article-title: Command filtered robust adaptive NN control for a class of uncertain strict-feedback nonlinear systems under input saturation publication-title: J. Frankl. Inst. – volume: 30 start-page: 3812 year: 2022 end-page: 3822 ident: bib0007 article-title: A novel mixed control approach for fuzzy systems via membership functions online learning policy publication-title: IEEE Trans. Fuzzy Syst. – volume: 64 start-page: 3046 year: 2019 end-page: 3053 ident: bib0023 article-title: Adaptive fixed-time control for MIMO nonlinear systems with asymmetric output constraints using universal barrier functions publication-title: IEEE Trans. Autom. Control – volume: 29 start-page: 5554 year: 2018 end-page: 5564 ident: bib0025 article-title: Adaptive neural control for robotic manipulators with output constraints and uncertainties publication-title: IEEE Trans. Neural Netw. Learn. Syst. – volume: 357 start-page: 11518 year: 2020 end-page: 11544 ident: bib0041 article-title: Observed-based adaptive finite-time tracking control for a class of nonstrict-feedback nonlinear systems with input saturation publication-title: J. Frankl. Inst. – volume: 73 start-page: 138 year: 2016 end-page: 144 ident: bib0009 article-title: Leader-following consensus for a class of high-order nonlinear multi-agent systems publication-title: Automatica – volume: 28 start-page: 4032 year: 2018 end-page: 4044 ident: bib0030 article-title: Stabilisation of state-and-input constrained nonlinear systems via diffeomorphisms: a Sontag’s formula approach with an actual application publication-title: Int. J. Robust Nonlinear Control – volume: 45 start-page: 918 year: 2009 end-page: 927 ident: bib0018 article-title: Barrier Lyapunov functions for the control of output-constrained nonlinear systems publication-title: Automatica – volume: 153 start-page: 159 year: 2015 end-page: 163 ident: bib0013 article-title: Adaptive controller design-based neural networks for output constraint continuous stirred tank reactor publication-title: Neurocomputing – volume: 103 start-page: 274 year: 2019 end-page: 281 ident: bib0012 article-title: Connectivity preservation and collision avoidance in networked nonholonomic multi-robot formation systems: unified error transformation strategy publication-title: Automatica – volume: 119 start-page: 109102 year: 2020 ident: bib0031 article-title: Control of nonlinear systems under dynamic constraints: a unified barrier function-based approach publication-title: Automatica – volume: 121 start-page: 109161 year: 2020 ident: 10.1016/j.jfranklin.2022.11.009_bib0015 article-title: Adaptive control allocation for constrained systems publication-title: Automatica doi: 10.1016/j.automatica.2020.109161 – volume: 30 start-page: 3812 issue: 9 year: 2022 ident: 10.1016/j.jfranklin.2022.11.009_bib0007 article-title: A novel mixed control approach for fuzzy systems via membership functions online learning policy publication-title: IEEE Trans. Fuzzy Syst. doi: 10.1109/TFUZZ.2021.3130201 – volume: 45 start-page: 918 issue: 4 year: 2009 ident: 10.1016/j.jfranklin.2022.11.009_bib0018 article-title: Barrier Lyapunov functions for the control of output-constrained nonlinear systems publication-title: Automatica doi: 10.1016/j.automatica.2008.11.017 – volume: 121 start-page: 109181 year: 2020 ident: 10.1016/j.jfranklin.2022.11.009_bib0021 article-title: Barrier Lyapunov function-based adaptive asymptotic tracking of nonlinear systems with unknown virtual control coefficients publication-title: Automatica doi: 10.1016/j.automatica.2020.109181 – volume: 66 start-page: 184 issue: 1 year: 2021 ident: 10.1016/j.jfranklin.2022.11.009_bib0004 article-title: Practical synchronization in networks of nonlinear heterogeneous agents with application to power systems publication-title: IEEE Trans. Autom. Control doi: 10.1109/TAC.2020.2981084 – volume: 53 start-page: 993 issue: 4 year: 2008 ident: 10.1016/j.jfranklin.2022.11.009_bib0016 article-title: Convex control systems and convex optimal control problems with constraints publication-title: IEEE Trans. Autom. Control doi: 10.1109/TAC.2008.919848 – volume: 18 start-page: 619 issue: 2 year: 2016 ident: 10.1016/j.jfranklin.2022.11.009_bib0036 article-title: Cooperative adaptive fuzzy output feedback control for synchronization of nonlinear multi-agent systems in the presence of input saturation publication-title: Asian J. Control doi: 10.1002/asjc.1104 – volume: 77 start-page: 133 year: 2017 ident: 10.1016/j.jfranklin.2022.11.009_bib0008 article-title: Distributed adaptive asymptotically consensus tracking control of nonlinear multi-agent systems with unknown parameters and uncertain disturbances publication-title: Automatica doi: 10.1016/j.automatica.2016.11.019 – volume: 37 start-page: 750 issue: 3 year: 2014 ident: 10.1016/j.jfranklin.2022.11.009_bib0017 article-title: Solving nonconvex optimal control problems by convex optimization publication-title: J. Guid., Control, Dyn. doi: 10.2514/1.62110 – volume: 357 start-page: 11518 issue: 16 year: 2020 ident: 10.1016/j.jfranklin.2022.11.009_bib0041 article-title: Observed-based adaptive finite-time tracking control for a class of nonstrict-feedback nonlinear systems with input saturation publication-title: J. Frankl. Inst. doi: 10.1016/j.jfranklin.2019.07.021 – volume: 46 start-page: 85 issue: 1 year: 2016 ident: 10.1016/j.jfranklin.2022.11.009_bib0019 article-title: Adaptive neural control of a class of output-constrained nonaffine systems publication-title: IEEE Trans. Cybern. doi: 10.1109/TCYB.2015.2394797 – volume: 458 start-page: 24 year: 2021 ident: 10.1016/j.jfranklin.2022.11.009_bib0029 article-title: Neural networks-based adaptive tracking control of multi-agent systems with output-constrained and unknown hysteresis publication-title: Neurocomputing doi: 10.1016/j.neucom.2021.05.079 – volume: 27 start-page: 39 issue: 1 year: 2019 ident: 10.1016/j.jfranklin.2022.11.009_bib0003 article-title: Event-triggered finite-time integral sliding mode controller for consensus-based formation of multirobot systems with disturbances publication-title: IEEE Trans. Control Syst. Technol. doi: 10.1109/TCST.2017.2757448 – volume: 153 start-page: 159 year: 2015 ident: 10.1016/j.jfranklin.2022.11.009_bib0013 article-title: Adaptive controller design-based neural networks for output constraint continuous stirred tank reactor publication-title: Neurocomputing doi: 10.1016/j.neucom.2014.11.041 – volume: 68 start-page: 294 year: 2016 ident: 10.1016/j.jfranklin.2022.11.009_bib0034 article-title: Global leader-following consensus of a group of general linear systems using bounded controls publication-title: Automatica doi: 10.1016/j.automatica.2016.01.027 – volume: 30 start-page: 4764 issue: 12 year: 2020 ident: 10.1016/j.jfranklin.2022.11.009_bib0044 article-title: Adaptive neural control for multiagent systems with asymmetric time-varying state constraints and input saturation publication-title: Int. J. Robust Nonlinear Control doi: 10.1002/rnc.5004 – volume: 50 start-page: 1530 issue: 4 year: 2020 ident: 10.1016/j.jfranklin.2022.11.009_bib0010 article-title: Global fixed-time consensus tracking of nonlinear uncertain multiagent systems with high-order dynamics publication-title: IEEE Trans. Cybern. doi: 10.1109/TCYB.2018.2879892 – start-page: 1 year: 2022 ident: 10.1016/j.jfranklin.2022.11.009_bib0006 article-title: Security-based fuzzy control for nonlinear networked control systems with dos attacks via a resilient event-triggered scheme publication-title: IEEE Trans. Fuzzy Syst. – volume: 64 start-page: 3046 issue: 7 year: 2019 ident: 10.1016/j.jfranklin.2022.11.009_bib0023 article-title: Adaptive fixed-time control for MIMO nonlinear systems with asymmetric output constraints using universal barrier functions publication-title: IEEE Trans. Autom. Control doi: 10.1109/TAC.2018.2874877 – volume: 357 start-page: 1090 issue: 2 year: 2020 ident: 10.1016/j.jfranklin.2022.11.009_bib0033 article-title: Distributed adaptive output consensus tracking for high-order nonlinear time-varying multi-agent systems with output constraints and actuator faults publication-title: J. Frankl. Inst. doi: 10.1016/j.jfranklin.2019.12.015 – volume: 51 start-page: 5577 issue: 9 year: 2021 ident: 10.1016/j.jfranklin.2022.11.009_bib0024 article-title: Adaptive intelligent control for input and output constrained high-order uncertain nonlinear systems publication-title: IEEE Trans. Syst., Man, Cybern. doi: 10.1109/TSMC.2019.2956063 – volume: 26 start-page: 1851 issue: 5 year: 2018 ident: 10.1016/j.jfranklin.2022.11.009_bib0011 article-title: Adaptive trajectory tracking control of a fully actuated surface vessel with asymmetrically constrained input and output publication-title: IEEE Trans. Control Syst. Technol. doi: 10.1109/TCST.2017.2728518 – volume: 28 start-page: 4032 issue: 13 year: 2018 ident: 10.1016/j.jfranklin.2022.11.009_bib0030 article-title: Stabilisation of state-and-input constrained nonlinear systems via diffeomorphisms: a Sontag’s formula approach with an actual application publication-title: Int. J. Robust Nonlinear Control doi: 10.1002/rnc.4119 – volume: 10 start-page: 509 issue: 5 year: 2016 ident: 10.1016/j.jfranklin.2022.11.009_bib0035 article-title: Distributed consensus tracking for non-linear multi-agent systems with input saturation: a command filtered backstepping approach publication-title: IET Control Theory Appl. doi: 10.1049/iet-cta.2015.0627 – volume: 81 start-page: 232 year: 2017 ident: 10.1016/j.jfranklin.2022.11.009_bib0020 article-title: Adaptive neural dynamic surface control of strict-feedback nonlinear systems with full state constraints and unmodeled dynamics publication-title: Automatica doi: 10.1016/j.automatica.2017.03.033 – volume: 357 start-page: 9709 issue: 14 year: 2020 ident: 10.1016/j.jfranklin.2022.11.009_bib0026 article-title: Asymmetric integral barrier Lyapunov function-based adaptive tracking control considering full-state with input magnitude and rate constraint publication-title: J. Frankl. Inst. doi: 10.1016/j.jfranklin.2020.07.037 – volume: 23 start-page: 340 issue: 1 year: 2015 ident: 10.1016/j.jfranklin.2022.11.009_bib0002 article-title: Time-varying formation control for unmanned aerial vehicles: theories and applications publication-title: IEEE Trans. Control Syst. Technol. doi: 10.1109/TCST.2014.2314460 – volume: 97 start-page: 64 year: 2018 ident: 10.1016/j.jfranklin.2022.11.009_bib0028 article-title: Distributed learning consensus for heterogenous high-order nonlinear multi-agent systems with output constraints publication-title: Automatica doi: 10.1016/j.automatica.2018.07.030 – year: 2021 ident: 10.1016/j.jfranklin.2022.11.009_bib0005 article-title: Sensor network based distributed state estimation for maneuvering target with guaranteed performances publication-title: Neurocomputing – volume: 119 start-page: 109102 year: 2020 ident: 10.1016/j.jfranklin.2022.11.009_bib0031 article-title: Control of nonlinear systems under dynamic constraints: a unified barrier function-based approach publication-title: Automatica doi: 10.1016/j.automatica.2020.109102 – volume: 29 start-page: 5554 issue: 11 year: 2018 ident: 10.1016/j.jfranklin.2022.11.009_bib0025 article-title: Adaptive neural control for robotic manipulators with output constraints and uncertainties publication-title: IEEE Trans. Neural Netw. Learn. Syst. doi: 10.1109/TNNLS.2018.2803827 – volume: 107 start-page: 194 year: 2020 ident: 10.1016/j.jfranklin.2022.11.009_bib0040 article-title: Consensus tracking of nonlinear multi-agent systems under input saturation with applications: a sector-based approach publication-title: ISA Trans. doi: 10.1016/j.isatra.2020.07.030 – volume: 64 start-page: 4972 issue: 6 year: 2017 ident: 10.1016/j.jfranklin.2022.11.009_bib0001 article-title: Recent advances in consensus of multi-agent systems: a brief survey publication-title: IEEE Trans. Ind. Electron. doi: 10.1109/TIE.2016.2636810 – volume: 80 start-page: 187 year: 2018 ident: 10.1016/j.jfranklin.2022.11.009_bib0037 article-title: Command filter based adaptive fuzzy bipartite output consensus tracking of nonlinear coopetition multi-agent systems with input saturation publication-title: ISA Trans. doi: 10.1016/j.isatra.2018.07.039 – volume: 41 start-page: 447 issue: 3 year: 1996 ident: 10.1016/j.jfranklin.2022.11.009_bib0042 article-title: Stable adaptive neural control scheme for nonlinear systems publication-title: IEEE Trans. Autom. Control doi: 10.1109/9.486648 – volume: 89 start-page: 653 issue: 4 year: 2016 ident: 10.1016/j.jfranklin.2022.11.009_bib0039 article-title: Adaptive periodic event-triggered consensus for multi-agent systems subject to input saturation publication-title: Int. J. Control doi: 10.1080/00207179.2015.1088967 – volume: 73 start-page: 138 year: 2016 ident: 10.1016/j.jfranklin.2022.11.009_bib0009 article-title: Leader-following consensus for a class of high-order nonlinear multi-agent systems publication-title: Automatica doi: 10.1016/j.automatica.2016.06.025 – volume: 295 start-page: 1 year: 2018 ident: 10.1016/j.jfranklin.2022.11.009_bib0027 article-title: Adaptive consensus control of output-constrained second-order nonlinear systems via neurodynamic optimization publication-title: Neurocomputing doi: 10.1016/j.neucom.2017.12.052 – volume: 478 start-page: 355 year: 2019 ident: 10.1016/j.jfranklin.2022.11.009_bib0038 article-title: Distributed adaptive output consensus tracking of nonlinear multi-agent systems via state observer and command filtered backstepping publication-title: Inf. Sci. doi: 10.1016/j.ins.2018.11.038 – volume: 355 start-page: 7548 issue: 15 year: 2018 ident: 10.1016/j.jfranklin.2022.11.009_bib0043 article-title: Command filtered robust adaptive NN control for a class of uncertain strict-feedback nonlinear systems under input saturation publication-title: J. Frankl. Inst. doi: 10.1016/j.jfranklin.2018.07.033 – volume: 63 start-page: 4008 issue: 11 year: 2018 ident: 10.1016/j.jfranklin.2022.11.009_bib0014 article-title: Triggering and control codesign in self-triggered modelpredictive control of constrained systems: with guaranteed performance publication-title: IEEE Trans. Autom. Control doi: 10.1109/TAC.2018.2810514 – volume: 46 start-page: 620 issue: 3 year: 2016 ident: 10.1016/j.jfranklin.2022.11.009_bib0022 article-title: Adaptive neural network control of an uncertain robot with full-state constraints publication-title: IEEE Trans. Cybern. doi: 10.1109/TCYB.2015.2411285 – volume: 103 start-page: 274 year: 2019 ident: 10.1016/j.jfranklin.2022.11.009_bib0012 article-title: Connectivity preservation and collision avoidance in networked nonholonomic multi-robot formation systems: unified error transformation strategy publication-title: Automatica doi: 10.1016/j.automatica.2019.02.019 – volume: 357 start-page: 6653 issue: 11 year: 2020 ident: 10.1016/j.jfranklin.2022.11.009_bib0032 article-title: Nonlinear mapping-based fixed-time stabilization of uncertain nonholonomic systems with time-varying state constraints publication-title: J. Frankl. Inst. doi: 10.1016/j.jfranklin.2020.04.028 |
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