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Chin. Phys. B, 2025, Vol. 34(6): 060202    DOI: 10.1088/1674-1056/adbee1
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An ADP-based robust control scheme for nonaffine nonlinear systems with uncertainties and input constraints

Shijie Luo(罗世杰)1, Kun Zhang(张坤)1,2,†, and Wenchao Xue(薛文超)3
1 The School of Astronautics, Beihang University, Beijing 100191, China;
2 The State Key Laboratory of High-Efficiency Reusable Aerospace Transportation Technology, Beijing 102206, China;
3 Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100190, China
Abstract  The paper develops a robust control approach for nonaffine nonlinear continuous systems with input constraints and unknown uncertainties. Firstly, this paper constructs an affine augmented system (AAS) within a pre-compensation technique for converting the original nonaffine dynamics into affine dynamics. Secondly, the paper derives a stability criterion linking the original nonaffine system and the auxiliary system, demonstrating that the obtained optimal policies from the auxiliary system can achieve the robust controller of the nonaffine system. Thirdly, an online adaptive dynamic programming (ADP) algorithm is designed for approximating the optimal solution of the Hamilton-Jacobi-Bellman (HJB) equation. Moreover, the gradient descent approach and projection approach are employed for updating the actor-critic neural network (NN) weights, with the algorithm's convergence being proven. Then, the uniformly ultimately bounded stability of state is guaranteed. Finally, in simulation, some examples are offered for validating the effectiveness of this presented approach.
Keywords:  adaptive dynamic programming      robust control      nonaffine nonlinear system      neural network  
Received:  20 December 2024      Revised:  17 February 2025      Accepted manuscript online:  11 March 2025
PACS:  02.30.Yy (Control theory)  
Fund: Project supported by the National Natural Science Foundation of China (Grant No. 62103408), Beijing Nova Program (Grant No. 20240484516), and the Fundamental Research Funds for the Central Universities (Grant No. KG16314701).
Corresponding Authors:  Kun Zhang     E-mail:  zhangkun22@buaa.edu.cn

Cite this article: 

Shijie Luo(罗世杰), Kun Zhang(张坤), and Wenchao Xue(薛文超) An ADP-based robust control scheme for nonaffine nonlinear systems with uncertainties and input constraints 2025 Chin. Phys. B 34 060202

[1] Silver D, Huang A, Maddison C, Guez A, Sifre L, Driessche G, Schrittwieser J, Antonoglou I, Panneershelvam V, Lanctot M, Dieleman S, Grewe D, Nham J, Kalchbrenner N, Sutskever I, Lillicrap T, Leach M, Kavukcuoglu K, Graepel T and Hassabis D 2016 Nature 529 484
[2] Silver D, Schrittwieser J, Simonyan K, Antonoglou I, Huang A, Guez A, Hubert T, Baker L, Lai M, Bolton A, Chen Y, Lillicrap T, Hui F, Sifre L, Driessche G, Graepel T and Hassabis D 2017 Nature 550 354
[3] Berner C, Brockman G, Chan B, Cheung V, Debiak P, Dennison C, Farhi D, Fischer Q, Hashme S, Hesse C, Józefowicz R, Gray S, Olsson C, Pachocki J W, Petrov M, de Oliveira Pinto H P, Raiman J, Salimans T, Schlatter J, Schneider J, Sidor S, Sutskever I, Tang J, Wolski F and Zhang S 2019 arXiv: 1912.06680
[4] Ozalp R, Ucar A and Guzelis C 2024 IEEE Access 12 51840
[5] Zhang R, Ishikawa A, Wang W, Striner B and Tonguz O K 2021 IEEE Transactions on Intelligent Transportation Systems 22 404
[6] Bokade R, Jin X and Amato C 2023 IEEE Access 11 47646
[7] Kaelbling L P, Littman M L and Moore A W 1996 J. Artif. Intell. Res. 4 237
[8] Ivanov S and D’yakonov A 2019 arXiv: 1906.10025
[9] Arulkumaran K, Deisenroth M P, Brundage M and Bharath A A 2017 IEEE Signal Processing Magazine 34 26
[10] Yang T, Tang H, Bai C, Liu J, Hao J, Meng Z, Liu P and Wang Z 2021 arXiv e-prints arXiv-2109
[11] Lyu X, Duan P, Duan Z and Zhang Z 2024 IEEE Transactions on Aerospace and Electronic Systems 60 632
[12] Lv X, Duan P and Duan Z 2021 International Journal of Robust and Nonlinear Control 31 496
[13] Lv X, Duan P, Duan Z and Song J 2021 International Journal of Robust and Nonlinear Control 31 7053
[14] Guo Y, Ma S and Shu C C 2024 Chin. Phys. B 33 024203
[15] Luo B, Liu D, Wu H N, Wang D and Lewis F L 2017 IEEE Transactions on Cybernetics 47 3341
[16] Zhang H, Zhang J, Yang G H and Luo Y 2015 IEEE Transactions on Fuzzy Systems 23 152
[17] Werbos P 1977 General Systems Yearbook 22 25
[18] Zhang K, Luo S, Wu H N and Su R 2025 IEEE Transactions on Aerospace and Electronic Systems
[19] Yang D, Li T, Xie X and Zhang H 2020 IEEE Transactions on Systems, Man, and Cybernetics: Systems 50 4086
[20] Zhang H, Su H, Zhang K and Luo Y 2019 IEEE Transactions on Fuzzy Systems 27 2202
[21] Zuo S, Song Y, Lewis F L and Davoudi A 2018 IEEE Transactions on Cybernetics 48 3197
[22] Zhang K, Su R, Zhang H and Tian Y 2021 IEEE Transactions on Neural Networks and Learning Systems 32 5502
[23] Wei Q L, Song R Z, Sun Q Y and Xiao W D 2015 Chin. Phys. B 24 090504
[24] Song R and Wei Q 2017 Chin. Phys. B 26 030505
[25] Qu Y H, Wang A N and Lin S 2018 Chin. Phys. B 27 010203
[26] Wang D, Gao N, Liu D, Li J and Lewis F L 2024 IEEECAA Journal of Automatica Sinica 11 18
[27] Yang X and Wang D 2024 IEEE Transactions on Neural Networks and Learning Systems
[28] Yang X and Wang D 2024 IEEE Transactions on Neural Networks and Learning Systems 36 6067
[29] Mu C, Zhang Y, Gao Z and Sun C 2020 IEEE Transactions on Systems, Man, and Cybernetics: Systems 50 4056
[30] Jiang Y and Jiang Z P 2012 IEEE Transactions on Circuits and Systems II: Express Briefs 59 693
[31] Lin F and Brandt R 1998 IEEE Transactions on Robotics and Automation 14 69
[32] Wang D, Mu C, He H and Liu D 2017 IEEE Transactions on Systems, Man, and Cybernetics: Systems 47 1358
[33] Zhao J, Na J and Gao G 2020 Neurocomputing 395 56
[34] Zhao J, Na J and Gao G 2022 Neurocomputing 471 21
[35] Ma Q, Jin P and Lewis F L 2024 IEEECAA Journal of Automatica Sinica 11 1447
[36] Fan Q Y and Yang G H 2017 ISA Transactions 66 122
[37] Murray J, Cox C, Lendaris G and Saeks R 2002 IEEE Transactions on Systems, Man, and Cybernetics: Part C Applications and Reviews 32 140
[38] Wei Q, Jiao S, Wang F Y and Dong Q 2024 IEEE Transactions on Cybernetics 54 4308
[39] Wei Q, Wang L, Lu J and Wang F Y 2022 IEEE Transactions on Systems, Man, and Cybernetics: Systems 52 192
[40] Lu J, Wei Q and Wang F Y 2020 IEEECAA Journal of Automatica Sinica 7 1662
[41] Bian T, Jiang Y and Jiang Z P 2014 Automatica 50 2624
[42] Zhang S, Zhao B and Zhang Y 2021 Neurocomputing 440 175
[43] Gong J and Yao B 2001 Automatica 37 1149
[44] Vamvoudakis K G and Lewis F L 2010 Automatica 46 878
[45] Wang D and Qiao J 2019 Neural Networks 117 1
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