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In order to overcome the difficulty in real-time effectively acquiring the target parameters of differential game guidance in a complex underwater environment,the differential game guidance of underwater nonlinear tracking control based on continuous time generalised predictive correction is proposed.Since the target parameter and the detection precision are seriously affected by the acoustic homing device detection period,noise,and interference,it is easy to lose or misjudge the target signal.Hence a combination of the dynamic tracking game model for differential games and the acoustic homing detection method of underwater tracking is used for making the on-line prediction and compensation correction to the deviation tendency of target manoeuvres deviating from the self-guided sound zero axis.This is carried out by using a continuous time generalized predictive control algorithm,according to the discrepancy between the predicted advance> and the expected value.The manoeuvring target can then be located in the maximum capture probability sector of the tracker device in real time.In order to solve the estimation difficulty problem of the remaining time of the dynamic differential game antagonism,and improve the response speed and the control precision of the system,the zero-efficiency control parameter and the predictive control algorithm are introduced to optimize the differential game.In this way,the infinite time domain differential game can be transformed into a multiple-time domain differential game with feedback correction.Through the complementing advantages of dynamic programming and predictive optimization,the real-time compensation and correction to the interceptor differential game guidance is realised,and the disadvantages of the differential game in the process constraints and stochastic disturbance are overcome. In order to adjust the favourable advance> of the self-guided detection rapidly,the learning prediction function of rolling optimization feedback correction is adopted.The initial moment of the differential response is pushed forward along with the entire forecast period by rolling optimization.To verify the validity of the algorithm,this is applied to the underwater nonlinear tracking game,and the guidance performance is compared with the differential game guidance and the integrated control algorithm of differential game and discrete predictive control.The results show that this can achieve the optimum control of the high precision underwater manoeuvring target on-line tracking and prediction correction with the detection mode limited in uncertain disturbances,because this is flexible in the choosing of sampling time and does not need control weighting for non-minimum phase system.This can also solve the problem of the initial bias and random disturbance taking into account the control constraints and interference suppression performance,and can improve the robustness to environmental interference.
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Keywords:
- continuous time generalized predictive control /
- tracking /
- differential game guidance /
- compensated correction
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[17] Zhang P, Fang Y W, Hui X B 2013 Acta Automatica Sin. 39 391 (in Chinese) [张平, 方洋旺, 惠晓滨 2013 自动化学报 39 391]
[18] Ping X B, Ding B C, Han C Z 2012 Acta Automatica Sin. 38 31 (in Chinese) [平续斌, 丁宝苍, 韩崇昭 2012 自动化学报 38 31]
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[1] Dong Z P, Wan L, Li Y M, Liu T 2015 Int. J. Nav. Arch. Ocean 7 817
[2] Qin J X, Katsnelson B, Li Z L, Zhang R H, Luo W 2016 Acta Acustica 41 145 (in Chinese) [秦继兴, Boris Katsnelson, 李整林, 张仁和, 骆文 2016 声学学报 41 145]
[3] Hu Z G, Li Z L, Zhang R H, Ren Y, Qin J X, He L 2016 Acta Phys. Sin. 65 014303 (in Chinese) [胡治国, 李整林, 张仁和, 任云, 秦继兴, 何利 2016 65 014303]
[4] Chen Y F, Li G J, Wang Z S, Zhang M W, Jia B 2013 Acta Phys. Sin. 62 084302 (in Chinese) [陈云飞, 李桂娟, 王振山, 张明伟, 贾兵 2013 62 084302]
[5] Shojaei K, Dolatshahi M 2017 Ocean Eng. 133 244
[6] Zhang P, Fang Y W, Zhang F M, Xiao B S 2012 Chinese J. Aeronaut. 25 739
[7] Zhang Y, Xu Q, Sun M W, Chen Z Q 2015 Acta Phys. Sin. 64 010502 (in Chinese) [张园, 徐琦, 孙明玮, 陈增强 2015 64 010502]
[8] Yu G F, Li D F, Qiu J M, Ye Y F 2016 Control Decis. 31 2013 (in Chinese) [余高锋, 李登峰, 邱锦明, 叶银芳 2016 控制与决策 31 2013]
[9] Wei H, Gao F, Wang D K, Wen G H, Pan L D 2007 J. Syst. Sim. 19 27 (in Chinese) [魏环, 高峰, 王东凯, 闻光辉, 潘立登 2007 系统仿真学报 19 27]
[10] Yong K H, Farouq S M, Hark K Y 2012 Chem. Eng. 84 479
[11] Oksendal B, Sulem A 2014 J. Optimiz. Theory Appl. 161 22
[12] Kamel O, Toufik R, Mohand O 2014 ISA Trasac. 53 76
[13] Chen Y, Zhang R M, Zhao X Y 2016 Ocean Eng. 15 123
[14] Zhang H G, Wei Q L, Liu D R 2011 Acta ?????? 47 207
[15] Fu Y, Chai Y 2015 Control Theory Appl. 32 196 (in Chinese) [富月, 柴佑 2015 控制理论与应用 32 196]
[16] Liu X D, Li K, Sun J, Fu X L, Zhang C H 2015 Control Theory Appl. 32 1640 (in Chinese) [刘旭东, 李柯, 孙静, 符晓玲, 张承慧 2015 控制理论与应用 32 1640]
[17] Zhang P, Fang Y W, Hui X B 2013 Acta Automatica Sin. 39 391 (in Chinese) [张平, 方洋旺, 惠晓滨 2013 自动化学报 39 391]
[18] Ping X B, Ding B C, Han C Z 2012 Acta Automatica Sin. 38 31 (in Chinese) [平续斌, 丁宝苍, 韩崇昭 2012 自动化学报 38 31]
[19] Krid M, Benamar F, Lenain R 2017 Int. J. Control Autom. 15 303
[20] Yan Z P, Liu Y B, Zhou J J, Zhang W, Wang L 2017 Chin. Phys. B 4 79
[21] Sarkar M, Nandy S, Vadal S R K 2016 Math. Comput. Simulat. 121 34
[22] Li H P, Yan W S, Shi Y 2017 Syst. Control Lett. 75 144
[23] Gao J, Liu C X 2015 J. Northwest Polytechnical Univ. 33 861 (in Chinese) [高剑, 刘昌鑫 2015 西北工业大学报 33 861]
[24] He J Z, Fu T P, Wu X H 2011 Comput. Dig. Eng. 39 21 (in Chinese) [何建忠, 傅调平, 吴晓海 2011 计算机与数字工程 39 21]
[25] Fan H, Zhang Y W, Li W Z 2008 J. Northwest Polytechnical Univ. 26 743 (in Chinese) [范辉, 张宇文, 李文哲 2008 西北工业大学学报 26 743]
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