Based on nonlinear failure criterion,a three-dimensional failure mechanism of the possible collapse of deep tunnel is presented with limit analysis theory.Support pressure is taken into consideration in the virtual wo...Based on nonlinear failure criterion,a three-dimensional failure mechanism of the possible collapse of deep tunnel is presented with limit analysis theory.Support pressure is taken into consideration in the virtual work equation performed under the upper bound theorem.It is necessary to point out that the properties of surrounding rock mass plays a vital role in the shape of collapsing rock mass.The first order reliability method and Monte Carlo simulation method are then employed to analyze the stability of presented mechanism.Different rock parameters are considered random variables to value the corresponding reliability index with an increasing applied support pressure.The reliability indexes calculated by two methods are in good agreement.Sensitivity analysis was performed and the influence of coefficient variation of rock parameters was discussed.It is shown that the tensile strength plays a much more important role in reliability index than dimensionless parameter,and that small changes occurring in the coefficient of variation would make great influence of reliability index.Thus,significant attention should be paid to the properties of surrounding rock mass and the applied support pressure to maintain the stability of tunnel can be determined for a given reliability index.展开更多
The hysteresis characteristic is the major deficiency in the positioning control of magnetic shape memory alloy actuator. A Prandtl-Ishlinskii model was developed to characterize the hysteresis of magnetic shape memor...The hysteresis characteristic is the major deficiency in the positioning control of magnetic shape memory alloy actuator. A Prandtl-Ishlinskii model was developed to characterize the hysteresis of magnetic shape memory alloy actuator. Based on the proposed Prandtl-Ishlinskii model, the inverse Prandtl-Ishlinskii model was established as a feedforward controller to compensate the hysteresis of the magnetic shape memory alloy actuator. For further improving of the positioning precision of the magnetic shape memory alloy actuator, a hybrid control method with hysteresis nonlinear model in feedforward loop was proposed. The control method is separated into two parts: a feedforward loop with inverse Prandtl-Ishlinskii model and a feedback loop with neural network controller. To validate the validity of the proposed control method, a series of simulations and experiments were researched. The simulation and experimental results demonstrate that the maximum error rate of open loop controller based on inverse PI model is 1.72%, the maximum error rate of the hybrid controller based on inverse PI model is 1.37%.展开更多
Single-axis rotation technique is often used in the marine laser inertial navigation system so as to modulate the constant biases of non-axial gyroscopes and accelerometers to attain better navigation performance.Howe...Single-axis rotation technique is often used in the marine laser inertial navigation system so as to modulate the constant biases of non-axial gyroscopes and accelerometers to attain better navigation performance.However,two significant accelerometer nonlinear errors need to be attacked to improve the modulation effect.Firstly,the asymmetry scale factor inaccuracy enlarges the errors of frequent zero-cross oscillating specific force measured by non-axial accelerometers.Secondly,the traditional linear model of accelerometers can hardly measure the continued or intermittent acceleration accurately.These two nonlinear errors degrade the high-precision specific force measurement and the calibration of nonlinear coefficients because triaxial accelerometers is urgent for the marine navigation.Based on the digital signal sampling property,the square coefficients and cross-coupling coefficients of accelerometers are considered.Meanwhile,the asymmetry scale factors are considered in the I-F conversion unit.Thus,a nonlinear model of specific force measurement is established compared to the linear model.Based on the three-axis turntable,the triaxial gyroscopes are utilized to measure the specific force observation for triaxial accelerometers.Considering the nonlinear combination,the standard calibration parameters and asymmetry factors are separately estimated by a two-step iterative identification procedure.Besides,an efficient specific force calculation model is approximately derived to reduce the real-time computation cost.Simulation results illustrate the sufficient estimation accuracy of nonlinear coefficients.The experiments demonstrate that the nonlinear model shows much higher accuracy than the linear model in both the gravimetry and sway navigation validations.展开更多
The electrode regulator system is a complex system with many variables, strong coupling and strong nonlinearity, while conventional control methods such as proportional integral derivative （PID） can not meet the req...The electrode regulator system is a complex system with many variables, strong coupling and strong nonlinearity, while conventional control methods such as proportional integral derivative （PID） can not meet the requirements. A robust adaptive neural network controller （RANNC） for electrode regulator system was proposed. Artificial neural networks were established to learn the system dynamics. The nonlinear control law was derived directly based on an input-output approximating method via the Taylor expansion, which avoids complex control development and intensive computation. The stability of the closed-loop system was established by the Lyapunov method. The current fluctuation relative percentage is less than ±8% and heating rate is up to 6.32 ℃/min when the proposed controller is used. The experiment results show that the proposed control scheme is better than inverse neural network controller （INNC） and PID controller （PIDC）.展开更多
基金Project (2013CB036004) supported by National Basic Research Program of China
文摘Based on nonlinear failure criterion,a three-dimensional failure mechanism of the possible collapse of deep tunnel is presented with limit analysis theory.Support pressure is taken into consideration in the virtual work equation performed under the upper bound theorem.It is necessary to point out that the properties of surrounding rock mass plays a vital role in the shape of collapsing rock mass.The first order reliability method and Monte Carlo simulation method are then employed to analyze the stability of presented mechanism.Different rock parameters are considered random variables to value the corresponding reliability index with an increasing applied support pressure.The reliability indexes calculated by two methods are in good agreement.Sensitivity analysis was performed and the influence of coefficient variation of rock parameters was discussed.It is shown that the tensile strength plays a much more important role in reliability index than dimensionless parameter,and that small changes occurring in the coefficient of variation would make great influence of reliability index.Thus,significant attention should be paid to the properties of surrounding rock mass and the applied support pressure to maintain the stability of tunnel can be determined for a given reliability index.
基金Project(51105170) supported by the National Natural Science Foundation of ChinaProject supported by the Scientific Research Foundation for the Returned Overseas Chinese Scholars,Ministry of Education,China
文摘The hysteresis characteristic is the major deficiency in the positioning control of magnetic shape memory alloy actuator. A Prandtl-Ishlinskii model was developed to characterize the hysteresis of magnetic shape memory alloy actuator. Based on the proposed Prandtl-Ishlinskii model, the inverse Prandtl-Ishlinskii model was established as a feedforward controller to compensate the hysteresis of the magnetic shape memory alloy actuator. For further improving of the positioning precision of the magnetic shape memory alloy actuator, a hybrid control method with hysteresis nonlinear model in feedforward loop was proposed. The control method is separated into two parts: a feedforward loop with inverse Prandtl-Ishlinskii model and a feedback loop with neural network controller. To validate the validity of the proposed control method, a series of simulations and experiments were researched. The simulation and experimental results demonstrate that the maximum error rate of open loop controller based on inverse PI model is 1.72%, the maximum error rate of the hybrid controller based on inverse PI model is 1.37%.
基金Project(61174002)supported by the National Natural Science Foundation of ChinaProject(200897)supported by the Foundation of National Excellent Doctoral Dissertation of PR China+1 种基金Project(NCET-10-0900)supported by the Program for New Century ExcellentTalents in University,ChinaProject(131061)supported by the Fok Ying Tung Education Foundation,China
文摘Single-axis rotation technique is often used in the marine laser inertial navigation system so as to modulate the constant biases of non-axial gyroscopes and accelerometers to attain better navigation performance.However,two significant accelerometer nonlinear errors need to be attacked to improve the modulation effect.Firstly,the asymmetry scale factor inaccuracy enlarges the errors of frequent zero-cross oscillating specific force measured by non-axial accelerometers.Secondly,the traditional linear model of accelerometers can hardly measure the continued or intermittent acceleration accurately.These two nonlinear errors degrade the high-precision specific force measurement and the calibration of nonlinear coefficients because triaxial accelerometers is urgent for the marine navigation.Based on the digital signal sampling property,the square coefficients and cross-coupling coefficients of accelerometers are considered.Meanwhile,the asymmetry scale factors are considered in the I-F conversion unit.Thus,a nonlinear model of specific force measurement is established compared to the linear model.Based on the three-axis turntable,the triaxial gyroscopes are utilized to measure the specific force observation for triaxial accelerometers.Considering the nonlinear combination,the standard calibration parameters and asymmetry factors are separately estimated by a two-step iterative identification procedure.Besides,an efficient specific force calculation model is approximately derived to reduce the real-time computation cost.Simulation results illustrate the sufficient estimation accuracy of nonlinear coefficients.The experiments demonstrate that the nonlinear model shows much higher accuracy than the linear model in both the gravimetry and sway navigation validations.
基金Project(N100604002) supported by the Fundamental Research Funds for Central Universities of ChinaProject(61074074) supported by the National Natural Science Foundation of China
文摘The electrode regulator system is a complex system with many variables, strong coupling and strong nonlinearity, while conventional control methods such as proportional integral derivative （PID） can not meet the requirements. A robust adaptive neural network controller （RANNC） for electrode regulator system was proposed. Artificial neural networks were established to learn the system dynamics. The nonlinear control law was derived directly based on an input-output approximating method via the Taylor expansion, which avoids complex control development and intensive computation. The stability of the closed-loop system was established by the Lyapunov method. The current fluctuation relative percentage is less than ±8% and heating rate is up to 6.32 ℃/min when the proposed controller is used. The experiment results show that the proposed control scheme is better than inverse neural network controller （INNC） and PID controller （PIDC）.
