Based on the development of the performance of magnetorheological damper,the tremor suppression strategy that uses angle displacement sensor and force sensor to sense the information of the tremor and uses the fuzzy neural network as the control algorithm is presented. The information of the maximum tremor torque can be achieved exactly by means fusing the data of displacement sensor and the data of force sensor. Due to the slow change of the maximum tremor torque,the fuzzy neural network with single input variable and single output variable is adopted as the control algorithm,and the mathematic model of fuzzy neural network is worked out. The elbow tremor suppression model is established to provide tremor information for fuzzy neural network training and tremor suppression strategy simulation,then the off-line fuzzy neural network training is finished with the selected training data set,and the tremor suppression strategy is simulated. Simulation results show that the tremor suppression strategy has presented is effectually for the tremor suppression.
Based on the performance of magnetorheological damper we have developed,a tremor suppression method using human limb nonrigid characteristic was presented.The tremor suppression machine was designed,and the measure part and the tremor suppression part were separated.Subsequently,the mathematic models of fuzzy neural network and elbow nonrigid tremor were worked out.Using selected training data set,the off-line fuzzy neural network training was finished.Then the tremor suppression method was simulated in Matlab.From the simulation results,it is found that the tremor suppression method has presented suppresses tremor effectively,and the tremor amplitude and tremor suppression torque can be controlled with angle displacement sensor.
