A novel qualitative control method to inverted pendulum systems

Abstract A new mathematical representation of qualitative concepts is presented by a cloud model in this paper. With the new model, a novel imitating-human control mechanism for inverted pendulum systems driven by single motor is proposed not only serving as foundations of qualitative control engine, but also integrating fuzziness and randomness in uncertainty reasoning. A case study is given to explore a good comprehensibility of human-intelligence control methods. The architecture and object-oriented programming of such a control engine to inverted pendulum systems based on cloud generators and qualitative rule constructors show the advantages in implementations. The physical experimental results with robustness are given and evaluated.

[1]  C.W. Anderson,et al.  Learning to control an inverted pendulum using neural networks , 1989, IEEE Control Systems Magazine.

[2]  K Furuta,et al.  Swing-up Control of Inverted Pendulum Using Pseudo-State Feedback , 1992 .

[3]  Xuemei Shi,et al.  Uncertainty reasoning based on cloud models in controllers , 1998 .

[4]  D. Saez,et al.  Design of fuzzy model based predictive controllers and its application to an inverted pendulum , 1997, Proceedings of 6th International Fuzzy Systems Conference.

[5]  K.J. Astrom,et al.  A nonlinear observer for the inverted pendulum , 1996, Proceeding of the 1996 IEEE International Conference on Control Applications IEEE International Conference on Control Applications held together with IEEE International Symposium on Intelligent Contro.

[6]  H. Unbehauen,et al.  Discrete computer control of a triple-inverted pendulum , 1990 .

[7]  T. Yamakawa.  Stablization of an inverted pendulum by a high-speed fuzzy logic controller hardware system , 1989 .