TY - GEN
T1 - A new fuzzy control and dynamic modeling of bicycle robot
AU - Li, Yangming
AU - Ren, Xuemei
AU - Liu, Jun
PY - 2012
Y1 - 2012
N2 - A dynamic model of bicycle robot is established based on the Lagrange method, and its motion features, which include nonlinear and parameter time-varying, are analyzed. A new fuzzy control is proposed to make the bicycle robot system achieve favorable control effects including good dynamic and steady-state performance. This new fuzzy control can be divided into two components. In the first part, the fuzzy control method, which is on the basis of the individual riding experience, is used to promote the dumping bicycle to swing back to the equilibrium position. In the second part, the adaptive fuzzy PID method is employed to eliminate static error and guarantee the bicycle robot no vibration near the equilibrium position. Concerning reliability of switching process, the fuzzy method of smooth switching is used to guarantee the steady transition between these two different control strategies. Since it is difficult to select the initial values of the adaptive fuzzy PID method, a modified particle swarm optimization (MPSO) method is utilized to optimize the initial parameters off-line. To show high efficiency and the accuracy of this proposed algorithm, simulation results demonstrate that the stability of bicycle robot can be guaranteed by using this design scheme.
AB - A dynamic model of bicycle robot is established based on the Lagrange method, and its motion features, which include nonlinear and parameter time-varying, are analyzed. A new fuzzy control is proposed to make the bicycle robot system achieve favorable control effects including good dynamic and steady-state performance. This new fuzzy control can be divided into two components. In the first part, the fuzzy control method, which is on the basis of the individual riding experience, is used to promote the dumping bicycle to swing back to the equilibrium position. In the second part, the adaptive fuzzy PID method is employed to eliminate static error and guarantee the bicycle robot no vibration near the equilibrium position. Concerning reliability of switching process, the fuzzy method of smooth switching is used to guarantee the steady transition between these two different control strategies. Since it is difficult to select the initial values of the adaptive fuzzy PID method, a modified particle swarm optimization (MPSO) method is utilized to optimize the initial parameters off-line. To show high efficiency and the accuracy of this proposed algorithm, simulation results demonstrate that the stability of bicycle robot can be guaranteed by using this design scheme.
KW - Bicycle robot
KW - Dynamic model
KW - New fuzzy control
UR - http://www.scopus.com/inward/record.url?scp=84868129790&partnerID=8YFLogxK
U2 - 10.1109/IHMSC.2012.109
DO - 10.1109/IHMSC.2012.109
M3 - Conference contribution
AN - SCOPUS:84868129790
SN - 9780769547213
T3 - Proceedings of the 2012 4th International Conference on Intelligent Human-Machine Systems and Cybernetics, IHMSC 2012
SP - 53
EP - 58
BT - Proceedings of the 2012 4th International Conference on Intelligent Human-Machine Systems and Cybernetics, IHMSC 2012
T2 - 2012 4th International Conference on Intelligent Human-Machine Systems and Cybernetics, IHMSC 2012
Y2 - 26 August 2012 through 27 August 2012
ER -