Hybrid Fuzzy-PID-based Control of a Twin Rotor MIMO System

This paper presents the development of a hybrid fuzzy-PID-based control approach for an experimental aerodynamic test rig-a twin rotor multi-input-multi-output system (TRMS). The control objective is to make the beam of the TRMS move quickly and accurately to the desired positions, i.e., the pitch and the yaw angles. Developing controller for this type of system is challenging due to the coupling effects between two axes and also due to its highly nonlinear characteristics. In this investigation accurate dynamic models of the system for both vertical and horizontal movements are developed first in order to get very similar responses to that of the real plant. These models are then used as test-beds to develop a set of hybrid-fuzzy PID controllers. The performance of the controllers in tracking movements in both vertical and horizontal planes are found to be very satisfactory in terms of accuracy, speed and the variations of reference signals. A comparative performance study of this hybrid fuzzy-PID control approach with respect to a single PID approach is also presented in this study

[1]  Emmanuel G. Collins,et al.  Fuzzy behavior navigation for an unmanned helicopter in unknown environments , 2005, 2005 IEEE International Conference on Systems, Man and Cybernetics.

[2]  Xiao Peng,et al.  Fuzzy behavior-based control of mobile robots , 2004, IEEE Transactions on Fuzzy Systems.

[3]  I.Z.M. Darus,et al.  Parametric modelling of a twin rotor system using genetic algorithms , 2004, First International Symposium on Control, Communications and Signal Processing, 2004..

[4]  E.N. Sanchez,et al.  Combining fuzzy and PID control for an unmanned helicopter , 2005, NAFIPS 2005 - 2005 Annual Meeting of the North American Fuzzy Information Processing Society.

[5]  H. Shim,et al.  A comprehensive study of control design for an autonomous helicopter , 1998, Proceedings of the 37th IEEE Conference on Decision and Control (Cat. No.98CH36171).

[6]  Kazuo Tanaka,et al.  A practical design approach to stabilization of a 3-DOF RC helicopter , 2004, IEEE Transactions on Control Systems Technology.

[7]  Jun Xiao,et al.  Fuzzy controller for wall-climbing microrobots , 2004, IEEE Transactions on Fuzzy Systems.

[8]  Andrew J. Chipperfield,et al.  Dynamic modeling and optimal control of a twin rotor MIMO system , 2000, Proceedings of the IEEE 2000 National Aerospace and Electronics Conference. NAECON 2000. Engineering Tomorrow (Cat. No.00CH37093).

[9]  M. Hasan Shaheed,et al.  Performance analysis of 4 types of conjugate gradient algorithms in the nonlinear dynamic modelling of a TRMS using feedforward neural networks , 2004, 2004 IEEE International Conference on Systems, Man and Cybernetics (IEEE Cat. No.04CH37583).

[10]  Jih-Gau Juang,et al.  Intelligent control scheme for twin rotor MIMO system , 2005, IEEE International Conference on Mechatronics, 2005. ICM '05..

[11]  Euntai Kim,et al.  Output feedback tracking control of robot manipulators with model uncertainty via adaptive fuzzy logic , 2004, IEEE Trans. Fuzzy Syst..

[12]  N. Ahmed,et al.  Controller design using fuzzy logic for a twin rotor MIMO system , 2003, 7th International Multi Topic Conference, 2003. INMIC 2003..

[13]  M. Sugeno,et al.  Development of an intelligent unmanned helicopter , 1995, Proceedings of 1995 IEEE International Conference on Fuzzy Systems..

[14]  Tzuu-Hseng S. Li,et al.  Fuzzy target tracking control of autonomous mobile robots by using infrared sensors , 2004, IEEE Transactions on Fuzzy Systems.

[15]  Dimiter Driankov,et al.  A fuzzy gain-scheduler for the attitude control of an unmanned helicopter , 2004, IEEE Transactions on Fuzzy Systems.