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Neural Computing and Applications
Erschienen in: Neural Computing and Applications 3-4/2014

01.03.2014 | Original Article

Optimal tracking control of a class of nonlinear discrete-time switched systems using adaptive dynamic programming

verfasst von: Chunbin Qin, Huaguang Zhang, Yanhong Luo

Erschienen in: Neural Computing and Applications | Ausgabe 3-4/2014

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Abstract

In this paper, an infinite-horizon optimal tracking control scheme is proposed for a class of nonlinear discrete-time switched systems. First, via system transformation, the optimal tracking problem is converted into designing an optimal regulator for the tracking error dynamics. And then, with convergence analysis in terms of value function and control policy, the iterative adaptive dynamic programming (ADP) algorithm is introduced to obtain the infinite-horizon optimal tracking controller which makes the value function close to its optimal value function. Next, two neural networks are used as parametric structures to implement the ADP algorithm, which aim at approximating the value function and the control policy, respectively. Finally, a simulation example is included to complement the theoretical discussions.
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Literatur
1.
2.
Borrelli F, Baotić M, Bemporad A, Morari M (2005) Dynamic programming for constrained optimal control of discrete-time linear hybrid systems. Automatica 41:1709–1721CrossRefMATH
3.
Chai T, Geng Z, Yue H, Wang H, Su C (2009) A hybrid intelligent optimal control method for complex flotation process. Int J Syst Sci 40:945–960CrossRef
4.
5.
Jiang B, Yang H, Shi P (2010) Switching fault tolerant control design via global dissipativity. Int J Syst Sci 41:1003–1012CrossRefMATHMathSciNet
6.
7.
Seatzu C, Corona D, Giua A, Bempoard A (2006) Optimal control of continuous time switched affine systems. IEEE Trans Autom Control 51:726–741CrossRef
8.
Du D, Jiang B, Shi P, Zhou S (2007) H\(\infty\) Filtering of discrete-time switched systems with state delays via switched lyapunov function approach. IEEE Trans Autom Control 52:1520–1525CrossRefMathSciNet
9.
Zhang L, Gao H (2010) Asynchronously switched control of switched linear systems with average dwell time. Automatica 46:953–958CrossRefMATH
10.
11.
Yu L, Fei S, Li X (2010) Robust adaptive neural tracking control for a class of switched affine nonlinear systems. Neurocomputing 73:2274–2279CrossRef
12.
Li Q, Zhao J, Dimirovski G (2009) Tracking control for switched time-varying delays systems with stabilizable and unstabilizable subsystems. Nonlinear Anal Hybrid Syst 3:133–142CrossRefMATHMathSciNet
13.
Wang M, Zhao J, Dimirovski G (2010) Output tracking control of nonlinear switched cascade systems using a variable structure control method. Int J Control 83(2):394–403CrossRefMATHMathSciNet
14.
Lin D, Wang X, Nian F, Zhang Y (2010) Dynamic fuzzy neural networks modeling and adaptive backstepping tracking control of uncertain chaotic systems. Neurocomputing 73:2873–2881CrossRef
15.
Lin D, Wang X, Yao Y (2012) Fuzzy neural adaptive tracking control of unknown chaotic systems with input saturation. Nonlinear Dyn 67(4):2889–2897CrossRefMATHMathSciNet
16.
Bellman RE (1957) Dynamic programming. Princeton University Press, PrincetonMATH
17.
Xu X-P, Antsaklis P-J (2003) Results and perspectives on computational methods for optimal control of switched systems. In: Maler O, Pnueli A (eds) Hybrid systems: computation and control (HSCC). Springer, Berlin, pp 540–555
18.
19.
Murray JJ, Cox CJ, Lendaris GG, Saeks R (2002) Adaptive dynamic programming. IEEE Trans Syst Man Cybern Part C Appl Rev 32:140–153CrossRef
20.
Wang FY, Zhang H, Liu D (2009) Adaptive dynamic programming: an introduction. IEEE Comput Intell Mag 43:9–47
21.
Si J, Wang YT (2001) On-line learning control by association and reinforcement. IEEE Trans Neural Netw 12:264–276CrossRef
22.
Al-Tamimi A, Lewis FL, Abu-Khalaf M (2008) Discrete-time nonlinear HJB solution using approximate dynamic programming: convergence proof. IEEE Trans Syst Man Cybern Part B Cybern 38:943–949CrossRef
23.
Bertsekas DP, Tsitsiklis JN (1996) Neuro-dynamic programming. Athena Scientific, BelmontMATH
24.
Prokhorov DV, Wunsch DC (1997) Adaptive critic designs. IEEE Trans Neural Netw 8:997–1007CrossRef
25.
Sutton RS, Barto AG (1998) Reinforcement learning: an introduction. The MIT Press, Cambridge
26.
Zhang H, Luo Y, Liu D (2009) Neural-network-based near-optimal control for a class of discrete-time affine nonlinear systems with control constraints. IEEE Trans Neural Netw 20:1490–1503CrossRef
27.
Zhang H, Cui L, Zhang X, Luo Y (2011) Data-driven robust approximate optimal tracking control for unknown general nonlinear systems using adaptive dynamic programming method. IEEE Trans Neural Netw 22:2226–2236CrossRef
28.
Cao N, Zhang H, Luo Y, Feng D (2011) Infinite horizon optimal control of affine nonlinear discrete switched systems using two-stage approximate dynamic programming. Int J Syst Sci. doi:10.​1080/​00207721.​2010.​549590
29.
Zhang H, Wei Q, Luo Y (2008) A novel infinite-time optimal tracking control scheme for a class of discrete-time nonlinear system based on greedy HDP iteration algorithm. IEEE Trans Syst Man Cybern Part B Cybern 38:937–942CrossRef
30.
Dierks T, Jagannathan S (2009) Optimal tracking control of affine nonlinear discrete-time systems with unknown internal dynamics. In: Proceedings of joint 48th IEEE conference on decision and control and 28th Chinese control conference. Shanghai, PR China, pp 6750–6755
31.
Wang D, Liu D, Wei Q (2012) Finite-horizon neuro-optimal tracking control for a class of discrete-time nonlinear systems using adaptive dynamic programming approach. Neurocomputing 78:14–22CrossRef
32.
Park Y, Choi M, Lee K (1996) An optimal tracking neuro-controller for nonlinear dynamic systems. IEEE Trans Neural Netw 7:1099–1110CrossRef
33.
Lin D, Wang X (2010) Observer-based decentralized fuzzy neural sliding mode control for interconnected unknown chaotic systems via network structure adaptation. Fuzzy Sets Syst 161(15):2066–2080CrossRefMATH
34.
Wang X, Zhao J (2010) Cryptanalysis on a parallel keyed hash function based on chaotic neural network. Neurocomputing 73:3224–3228CrossRef
35.
Lin D, Wang X (2011) Self-organizing adaptive fuzzy neural control for the synchronization of uncertain chaotic systems with random-varying parameters. Neurocomputing 74:2241–2249CrossRef
Metadaten
Titel
Optimal tracking control of a class of nonlinear discrete-time switched systems using adaptive dynamic programming
verfasst von
Chunbin Qin
Huaguang Zhang
Yanhong Luo
Publikationsdatum
01.03.2014
Verlag
Springer London
Erschienen in
Neural Computing and Applications / Ausgabe 3-4/2014
Print ISSN: 0941-0643
Elektronische ISSN: 1433-3058
DOI
https://doi.org/10.1007/s00521-012-1238-1

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