An Adaptive Fuzzy Control Approach for the Robust Tracking of a MEMS Gyroscope Sensor

In this paper, a direct adaptive fuzzy control using a supervisory compensator is designed for the robust tracking of a MEMS gyroscope sensor. The parameters of the membership functions are adjusted according to the designed adaptive law for the purpose of tracking a reference trajectory. A fuzzy controller that can approximate the unknown nonlinear function and compensate the system's nonlinearities is incorporated into the adaptive control scheme in the Lyapunov framework. A supervisory compensator is adopted to guarantee the stability of the closed loop system. Numerical simulations for a MEMS angular velocity sensor are investigated in order to verify the effectiveness of the proposed adaptive fuzzy control scheme and show that the system using the designed fuzzy controller with a supervisory compensator has better tracking performance and robustness than that using only a fuzzy control without a supervisory compensator in the presence of external disturbances.

[1]  Hyeongcheol Lee,et al.  Robust Adaptive Fuzzy Control by Backstepping for a Class of MIMO Nonlinear Systems , 2011, IEEE Transactions on Fuzzy Systems.

[2]  Roberto Oboe,et al.  Automatic Mode Matching in MEMS Vibrating Gyroscopes Using Extremum-Seeking Control , 2009, IEEE Transactions on Industrial Electronics.

[3]  Byung Kook Yoo,et al.  Adaptive control of robot manipulator using fuzzy compensator , 2000, IEEE Trans. Fuzzy Syst..

[4]  Young-Kiu Choi,et al.  An adaptive neurocontroller using RBFN for robot manipulators , 2004, IEEE Trans. Ind. Electron..

[5]  Shengyuan Xu,et al.  Adaptive Output-Feedback Fuzzy Tracking Control for a Class of Nonlinear Systems , 2011, IEEE Transactions on Fuzzy Systems.

[6]  Jin Bae Park,et al.  Adaptive Neural Sliding Mode Control of Nonholonomic Wheeled Mobile Robots With Model Uncertainty , 2009, IEEE Transactions on Control Systems Technology.

[7]  Niu Lin,et al.  Design and stability of indirect adaptive control for nonlinear system , 2013, Proceedings of the 32nd Chinese Control Conference.

[8]  Juntao Fei Robust adaptive vibration tracking control for a micro-electro-mechanical systems vibratory gyroscope with bound estimation , 2010 .

[9]  Peng-Yung Woo,et al.  An adaptive fuzzy sliding mode controller for robotic manipulators , 2003, IEEE Trans. Syst. Man Cybern. Part A.

[10]  Roberto Horowitz,et al.  Trajectory-Switching Algorithm for a MEMS Gyroscope , 2007, IEEE Transactions on Instrumentation and Measurement.

[11]  Celal Batur,et al.  A novel adaptive sliding mode control with application to MEMS gyroscope. , 2009, ISA transactions.

[12]  Robert Patton Leland,et al.  Adaptive control of a MEMS gyroscope using Lyapunov methods , 2006, IEEE Transactions on Control Systems Technology.

[13]  Rong-Jong Wai,et al.  Adaptive Fuzzy Neural Network Control Design via a T–S Fuzzy Model for a Robot Manipulator Including Actuator Dynamics , 2008, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[14]  Li-Xin Wang,et al.  Adaptive fuzzy systems and control - design and stability analysis , 1994 .

[15]  P. X. Liu,et al.  Robust Adaptive Fuzzy Output Feedback Control System for Robot Manipulators , 2011, IEEE/ASME Transactions on Mechatronics.

[16]  Rong-Jong Wai,et al.  Fuzzy Sliding-Mode Control Using Adaptive Tuning Technique , 2007, IEEE Transactions on Industrial Electronics.

[17]  Celal Batur,et al.  Sliding mode control of a simulated MEMS gyroscope. , 2006 .

[18]  Sangkyung Sung,et al.  On the Mode-Matched Control of MEMS Vibratory Gyroscope via Phase-Domain Analysis and Design , 2009, IEEE/ASME Transactions on Mechatronics.