For the purpose of improving fault detection accuracy of aero-engine distributed control system, an optimal design method based on chaos adaptive artificial fish swarm algorithm for distributed control system fault detection observer was proposed. First, in order to better simulate the actual distributed control system, dual channel multiple packet transmission was converted to switching system and short time-varying delay was modeled as an uncertainty in system models. Then, a fault observer is designed to obtain the state-space model of error system and the chaos adaptive artificial fish swarm algorithm is introduced. Furthermore, the ratio value of the residual signal transfer function, respectively, to the unknown disturbance signal and fault signal, are regarded as the objective function, and the minimum of the objective function is optimized to get the optimal observer matrix by chaos adaptive artificial fish swarm algorithm with the constraint of error system stability. Finally, the structure and operating principle of aero-engine distributed control system semi-physical platform is introduced, and comparison is made between the simulation of fault detection optimization method and the tradition robust fault detection method on the platform. The simulation results verify that the proposed method can efficiently reduce fault positive ratio and fault negative ratio simultaneously, which can expand the selection scope of threshold value and improve accuracy of fault detection.
KazempourFGhaisariJ. Stability analysis of model-based networked distributed control systems. J Process Contr2013; 23: 444–452.
2.
BelapurkarRKYedavalliRK. Stability of fiber optic networked decentralized distributed engine control under time delays. In: Proceedings of the 45th AIAA/ASME/SAE/ASEE joint propulsion conference, Denver, CO, 2–5 August 2009, pp.1–8. Reston, VA: AIAA.
3.
KazempourMMosbahiO. Intelligent distributed control systems. Inform Soft Technol2010; 52(12): 1259–1271.
4.
WeiMXZhenGX. Robust fault detection for a class of uncertain switched nonlinear systems via the state updating approach. Nonlinear Anal: Hybi2014; 12: 132–146.
5.
WangZHRodriguesMTheilliolDet al. Actuator fault estimation observer design for discrete-time linear parameter-varying descriptor systems. Int J Adapt Control2015; 29(2): 242–258.
6.
RachanaAGMoYC. Networked control system: overview and research trends. IEEE T Ind Electron2010; 57(7): 2527–2536.
7.
DongHLWangZDLamJet al. Fuzzy-model-based robust fault detection with stochastic mixed time delays and successive packet dropouts. IEEE T Syst Man Cy B2012; 42(2): 365–376.
8.
KargarSMSalahshoorKYazdanpanahMJ. Integrated nonlinear model predictive fault tolerant control and multiple model based fault detection and diagnosis. Chem Eng Res Des2014; 92(2): 340–349.
9.
LiZSuHGuYet al. H∞ filtering for discrete-time singular networked systems with communication delays and data missing. Int J Syst Sci2013; 44(4): 604–614.
10.
ZhangYFangH. Stabilization of nonlinear networked systems with sensor random packet dropout and time-varying delay. Appl Math Modell2011; 35: 2253–2264.
11.
WuJLYangSH. Stabilizing controller design for discrete-time networked control systems under a multiple-packet sequential transmission policy. Asian J Control2013; 15(5): 1555–1561.
12.
YuJYWangL. A new approach to controller design for networked control systems with multiple-packet transmissions. Syst Contr Commun2011; 3(2): 158–177.
13.
MeiYYuanXDXiaoWD. A switched system approach to robust stabilization of networked control systems with multiple-packet transmission. Asian J Control2015; 17(4): 1415–1423.
14.
MeiXZhenGX. Robust fault detection for switched positive linear systems with time varying delays. ISA Trans2014; 53(1): 10–16.
15.
HuangSNTanKK. Fault detection, isolation, and accommodation control in robotic systems. IEEE T Energy Conver2008; 5(3): 480–489.
SongYDLuYGanZX. Descriptor sliding mode approach for fault reconstruction and fault-tolerant control of nonlinear uncertain systems. Inform Sci2016; 367–368: 194–208.
18.
LiuMShiP. Sensor fault estimation and tolerant control for ito stochastic systems with a descriptor sliding mode approach. Automatica2013; 49(5): 1242–1250.
19.
ParkTG. Designing fault detection observers for linear systems with mismatched unknown inputs. J Process Contr2013; 23: 1185–1196.
20.
SaeedAJafarZHamidRK. Robust unknown input observer design for linear uncertain time delay systems with application to fault detection. Asian J Control2014; 16(4): 1006–1019.
21.
PiotrWMarcinMKrzysztofPet al. A neural-network-based robust observer for simultaneous unknown input decoupling and fault estimation. Cham: Springer, 2015, pp.535–545.
22.
GuoSHZhu XuLY. Unknown input observer design for Takagi-Sugeno fuzzy stochastic system. Int J Control Autom2015; 13(4): 1003–1009.
23.
WangJWShenYWangZH. H−/H∞ fault detection filter design for interval time-varying delays switched systems. J Syst Eng Electron2016; 27(4): 878–886.
24.
ChuXLZhuYShiJT. Image edge detection based on improved artificial fish-school swarm algorithm. Comput Syst Appl2010; 19(8): 173–176.
25.
LiXLShaoZJQianJX. An optimizing method based on autonomous animate: fish swarm algorithm. Proc Syst Eng Theory Pract2002; 11(22): 32–38.
26.
JiangMYYuanDF. Artificial fish swarm algorithm and its applications. In: Proceedings of the international conference on sensing, computing and automation, Chongqing China, 8–11 May 2006, pp.1782–1787.
27.
HeYYXuQFYangSLet al. Reservoir flood operation based on chaotic partial swarm optimization algorithm. Appl Math Modell2014; 38: 4480–4492.
28.
LiMSHuangXYLiuHSet al. Prediction of the gas solubility in polymers by a radial basis function neural network based on chaotic self-adaptive particle swarm optimization and a cluster method. J Appl Polym Sci2013; 130(5): 3825–3832.
29.
LiMWKangHGZhouPFet al. Hybrid optimization algorithm based on chaos, cloud and particle swarm optimization algorithm. J Syst Eng Electron2013; 24(2): 324–334.
30.
SheikholeslamiRKavehA. A survey of chaos embedded meta-heuristic algorithm. Int J Optimiz Civil Eng2013; 3(4): 617–633.
31.
HuaZYZhouYCPunCMet al. 2D sine logistic modulation map for image encryption. Inform Sci2015; 297(1): 80–94.
32.
ZhengYFangHJWangHet al. Fault detection approach for networked control system based on memoryless reduced-order observer. ACTA Automat Sin2003; 29(4): 559–566.
33.
WangBZhangHBWangGet al. Asynchronous control of discrete-time impulsive switched systems with mode-dependent average dwell time. ISA Trans2014; 53(2): 367–372.
34.
LiuHZhaoXD. Finite-time H∞ control of switched systems with mode-dependent average dwell time. J Frankl Inst2014; 351(3): 1301–1315.
35.
GaoZ. Fault estimation and fault-tolerant control for discrete-time dynamic systems. IEEE T Ind Electron2015; 62(6): 3874–3884.
36.
NeshatMSepidnamGSargolzaeiMet al. Artificial fish swarm algorithm: a survey of the state-of-the-art, hybridization, combinatorial and indicative applications. Artif Intell Rev2014; 42: 965–974.
37.
ZhangPDingSX. Disturbance decoupling in fault detection of linear periodic systems. Automatica2007; 43(8): 1410–1417.
38.
ChenYXueAKLuRQet al. Delay-dependent robust H∞ guaranteed cost filtering for uncertain systems with distributed. IEEE Conf Ind Electron Appl2007; 7: 2908–2912.
