A practical design approach to stabilization of a 3-DOF RC helicopter

This paper presents a practical design approach to the stabilization of a three degrees of freedom (3-DOF) RC helicopter. First, the nonlinear model of the RC helicopter is constructed. To facilitate control design, a simplified version of the nonlinear model is derived. A Takagi-Sugeno fuzzy model is then constructed to represent the simplified nonlinear model. The control purpose is to stabilize the RC helicopter while taking into account practical performance considerations in terms of good speed of response and small control effort. To achieve the control objective, we impose a decay rate condition to ensure a good speed of response and an input constraint condition to avoid actuator saturations in the control design. Both conditions are represented in terms of linear matrix inequalities (LMIs). By simultaneously solving them, we render a stabilizing fuzzy controller that achieves good speed of response with small control effort. However, the controller designed for the simplified model can not always stabilize the original nonlinear model due to discrepancies introduced via the simplification process. To overcome this limitation, we design a robust fuzzy controller to compensate for the modeling discrepancies. The resulting robust stability condition with good speed of response is represented in terms of LMIs. By simultaneously solving this condition together with an input constraint condition, we arrive at a robust stabilizing fuzzy controller that achieves good speed of response without actuator saturations. Both simulation and experimental results are included to demonstrate the viability and applicability of the approach.

[1]  T. Hori,et al.  Stable control for R/C helicopter , 2001, Proceedings Joint 9th IFSA World Congress and 20th NAFIPS International Conference (Cat. No. 01TH8569).

[2]  Guanrong Chen,et al.  Fuzzy PID controller: Design, performance evaluation, and stability analysis , 2000, Inf. Sci..

[3]  Kazuo Tanaka,et al.  Parallel distributed compensation of nonlinear systems by Takagi-Sugeno fuzzy model , 1995, Proceedings of 1995 IEEE International Conference on Fuzzy Systems..

[4]  Michio Sugeno,et al.  Fuzzy identification of systems and its applications to modeling and control , 1985, IEEE Transactions on Systems, Man, and Cybernetics.

[5]  S. Hong Synthesis of an LMI-based fuzzy control system with guaranteed optimal H/sub /spl infin// performance , 1998, 1998 IEEE International Conference on Fuzzy Systems Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98CH36228).

[6]  Kazuo Tanaka,et al.  Fuzzy regulators and fuzzy observers: relaxed stability conditions and LMI-based designs , 1998, IEEE Trans. Fuzzy Syst..

[7]  Kazuo Tanaka,et al.  An approach to fuzzy control of nonlinear systems: stability and design issues , 1996, IEEE Trans. Fuzzy Syst..

[8]  Kazuo Tanaka,et al.  Robust stabilization of a class of uncertain nonlinear systems via fuzzy control: quadratic stabilizability, H∞ control theory, and linear matrix inequalities , 1996, IEEE Trans. Fuzzy Syst..

[9]  Kazuo Tanaka,et al.  Fuzzy Control Systems Design and Analysis: A Linear Matrix Inequality Approach , 2008 .

[10]  Dimitar Petrov Filev Algebraic design of fuzzy logic controllers , 1996, Proceedings of the 1996 IEEE International Symposium on Intelligent Control.

[11]  Michio Sugeno,et al.  Intelligent Control of an Unmanned Helicopter Based on Fuzzy Logic , 1995 .

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

[13]  H. T. Nguyen Development of an Intelligent Unmanned Helicopter , 1999 .

[14]  Kazuo Tanaka,et al.  Stability analysis and design of fuzzy control systems , 1992 .

[15]  Reza Langari,et al.  Building Sugeno-type models using fuzzy discretization and orthogonal parameter estimation techniques , 1995, IEEE Trans. Fuzzy Syst..

[16]  S. Farinwata,et al.  Stability analysis of the fuzzy logic controller designed by the phase portrait assignment algorithm , 1993, [Proceedings 1993] Second IEEE International Conference on Fuzzy Systems.

[17]  Masayoshi Tomizuka,et al.  A framework for analysis and synthesis of fuzzy linguistic control systems , 1991 .

[18]  Kazuo Tanaka,et al.  Model construction, rule reduction, and robust compensation for generalized form of Takagi-Sugeno fuzzy systems , 2001, IEEE Trans. Fuzzy Syst..