A neural network-based sliding-mode control for rotating stall and surge in axial compressors

A decoupled sliding-mode neural network variable-bound control system (DSMNNVB) is proposed to control rotating stall and surge in jet engine compression systems in presence of disturbance and uncertainty. The control objective is to drive the system state to the original equilibrium point and it proves that the control system is asymptotically stable. In this controller, an adaptive neural network (NN) control scheme is employed for unknown dynamic of nonlinear plant without using a model of the plant. Moreover, no prior knowledge of the plant is assumed. The proposed DSMNNVB controller ensures Lyapunov stability of the nonlinear dynamic of the system.

[1]  Nader Nariman-zadeh,et al.  Modelling of multiple short-length-scale stall cells in an axial compressor using evolved GMDH neural networks , 2008 .

[2]  Ahmad Bagheri,et al.  An adaptive neuro-fuzzy sliding mode based genetic algorithm control system for under water remotely operated vehicle , 2010, Expert Syst. Appl..

[3]  Li-Xin Wang,et al.  A Course In Fuzzy Systems and Control , 1996 .

[4]  Chun-Yi Su,et al.  A sliding mode controller with bound estimation for robot manipulators , 1993, IEEE Trans. Robotics Autom..

[5]  F. Moore,et al.  A Theory of Post-Stall Transients in Axial Compression Systems: Part II—Application , 1986 .

[6]  Ahmad Bagheri,et al.  Simulation and tracking control based on neural-network strategy and sliding-mode control for underwater remotely operated vehicle , 2009, Neurocomputing.

[7]  Alexander Leonessa,et al.  Nonlinear robust disturbance rejection controllers for rotating stall and surge in axial flow compressors , 1999, IEEE Trans. Control. Syst. Technol..

[8]  Frank L. Lewis,et al.  Multilayer neural-net robot controller with guaranteed tracking performance , 1996, IEEE Trans. Neural Networks.

[9]  Rong-Jong Wai,et al.  Tracking control based on neural network strategy for robot manipulator , 2003, Neurocomputing.

[10]  Hongnian Yu,et al.  Variable structure adaptive control of robot manipulators , 1997 .

[11]  Hong Wang,et al.  A direct adaptive neural-network control for unknown nonlinear systems and its application , 1998, IEEE Trans. Neural Networks.

[12]  Frank L. Lewis,et al.  Control of Robot Manipulators , 1993 .

[13]  Ahmad Bagheri,et al.  Decoupled adaptive neuro-fuzzy (DANF) sliding mode control system for a Lorenz chaotic problem , 2009, Expert Syst. Appl..

[14]  Lon-Chen Hung,et al.  Decoupled control using neural network-based sliding-mode controller for nonlinear systems , 2007, Expert Syst. Appl..

[15]  F. Moore.  A Theory of Rotating Stall of Multistage Axial Compressors: Part II—Finite Disturbances , 1984 .

[16]  Chuen-Chien Lee.  FUZZY LOGIC CONTROL SYSTEMS: FUZZY LOGIC CONTROLLER - PART I , 1990 .

[17]  Henrik Schiøler,et al.  Proceedings of the 2006 IEEE International Conference on Control Applications , 2006 .

[18]  Nicholas A. Cumpsty,et al.  Prediction of Compressor Performance in Rotating Stall , 1978 .

[19]  Chin-Teng Lin,et al.  Neural fuzzy systems , 1994 .

[20]  Jan Tommy Gravdahl,et al.  Compressor Surge and Rotating Stall: Modeling and Control , 1998 .

[21]  Frank L. Lewis,et al.  Optimal design of CMAC neural-network controller for robot manipulators , 2000, IEEE Trans. Syst. Man Cybern. Part C.

[22]  B. de Jager,et al.  Modeling and control of rotating stall and surge: an overview , 1998, Proceedings of the 1998 IEEE International Conference on Control Applications (Cat. No.98CH36104).

[23]  Rong-Jong Wai,et al.  Ultrasonic motor servo-drive with online trained neural-network model-following controller , 1998 .