The accuracy of an articulated torque analysis influences the comprehensive performances of heavy-duty multi-legged robots. Currently, the extremal estimation method and some complex methods are employed to calculate ...The accuracy of an articulated torque analysis influences the comprehensive performances of heavy-duty multi-legged robots. Currently, the extremal estimation method and some complex methods are employed to calculate the articulated torques, which results in a large safety margin or a large number of calculations. To quickly obtain accurate articulated torques, an analysis method for the articulated torque is presented for an electrically driven heavy-duty six-legged robot. First, the rearmost leg that experiences the maximum normal contact force is confirmed when the robot transits a slope. Based on the ant-type and crab-type tripod gaits, the formulas of classical mechanics and MATLAB software are employed to theoretically analyze the relevant static torques of the joints. With the changes in the joint angles for the abductor joint, hip joint, and knee joint, variable tendency charts and extreme curves are obtained for the static articulated torques. Meanwhile, the maximum static articulated torques and the corresponding poses of the robot are also obtained. According to the poses of the robot under the maximum static articulated torques, ADAMS software is used to carry out a static simulation analysis. Based on the relevant simulation curves of the articulated torques, the maximum static articulated torques are acquired. A comparative analysis of the maximum static articulated torques shows that the theoretical calculation values are higher than the static simulation values, and the maximum error value is approximately 10%. The proposed method lays a foundation for quickly determining accurate articulated torques to develop heavy-duty six-legged robots.展开更多
A principal component analysis-cerebellar model articulation controller （PCA-CMAC） model is proposed for machine performance degradation assessment.PCA is used to feature selection,which eliminates the redundant inf...A principal component analysis-cerebellar model articulation controller （PCA-CMAC） model is proposed for machine performance degradation assessment.PCA is used to feature selection,which eliminates the redundant information among the features from the sensor signals and reduces the dimension of the input to CMAC.CMAC is used to assess degradation states quantitatively based on its local generalization ability.The implementation of the model is presented and the model is applied in a drilling machine to assess the states of the cutting tool. The results show that the model can assess the wear states quantitatively based on the normal state of the cutting tool.The influence of the quantization parameter g and the generalization parameter r in the CMAC model on the assessment results is analyzed.If g is larger,the generalization ability is better,but the difference of degradation states is not obvious.If r is smaller,the different states are distinct,but memory requirements for storing the weights are larger.The principle for selecting two parameters is that the memory storing the weights should be small while the degradation states should be easily distinguished.展开更多
基金supported by National Basic Research Program of China(973 Program, Grant No. 2013CB035502)International Science and Technology Cooperation Project with Russia (Grant No. 2010DFR70270)+2 种基金National Natural Science Foundation of China (Grant No. 51275106)"111" Project (Grant No. B07018)Key Laboratory Opening Funding of Aerospace Mechanism and Control, China (Grant No. HIT. KLOF.2010057)
文摘The accuracy of an articulated torque analysis influences the comprehensive performances of heavy-duty multi-legged robots. Currently, the extremal estimation method and some complex methods are employed to calculate the articulated torques, which results in a large safety margin or a large number of calculations. To quickly obtain accurate articulated torques, an analysis method for the articulated torque is presented for an electrically driven heavy-duty six-legged robot. First, the rearmost leg that experiences the maximum normal contact force is confirmed when the robot transits a slope. Based on the ant-type and crab-type tripod gaits, the formulas of classical mechanics and MATLAB software are employed to theoretically analyze the relevant static torques of the joints. With the changes in the joint angles for the abductor joint, hip joint, and knee joint, variable tendency charts and extreme curves are obtained for the static articulated torques. Meanwhile, the maximum static articulated torques and the corresponding poses of the robot are also obtained. According to the poses of the robot under the maximum static articulated torques, ADAMS software is used to carry out a static simulation analysis. Based on the relevant simulation curves of the articulated torques, the maximum static articulated torques are acquired. A comparative analysis of the maximum static articulated torques shows that the theoretical calculation values are higher than the static simulation values, and the maximum error value is approximately 10%. The proposed method lays a foundation for quickly determining accurate articulated torques to develop heavy-duty six-legged robots.
基金The National Natural Science Foundation of China(No.60443007,50390063).
文摘A principal component analysis-cerebellar model articulation controller （PCA-CMAC） model is proposed for machine performance degradation assessment.PCA is used to feature selection,which eliminates the redundant information among the features from the sensor signals and reduces the dimension of the input to CMAC.CMAC is used to assess degradation states quantitatively based on its local generalization ability.The implementation of the model is presented and the model is applied in a drilling machine to assess the states of the cutting tool. The results show that the model can assess the wear states quantitatively based on the normal state of the cutting tool.The influence of the quantization parameter g and the generalization parameter r in the CMAC model on the assessment results is analyzed.If g is larger,the generalization ability is better,but the difference of degradation states is not obvious.If r is smaller,the different states are distinct,but memory requirements for storing the weights are larger.The principle for selecting two parameters is that the memory storing the weights should be small while the degradation states should be easily distinguished.
