A dissipative-based adaptive neural control scheme was developed for a class of nonlinear uncertain systems with unknown nonlinearities that might not be linearly parameterized. The major advantage of the present work...A dissipative-based adaptive neural control scheme was developed for a class of nonlinear uncertain systems with unknown nonlinearities that might not be linearly parameterized. The major advantage of the present work was to relax the requirement of matching condition, i.e., the unknown nonlinearities appear on the same equation as the control input in a state-space representation, which was required in most of the available neural network controllers. By synthesizing a state-feedback neural controller to make the closed-loop system dissipative with respect to a quadratic supply rate, the developed control scheme guarantees that the L2-gain of controlled system was less than or equal to a prescribed level. And then, it is shown that the output tracking error is uniformly ultimate bounded. The design scheme is illustrated using a numerical simulation.展开更多
Raveling is a common distress of asphalt pavements,defined as the removal of stones from the pavement surface.To predict and assess raveling quantitatively,a cumulative damage model based on an energy dissipation appr...Raveling is a common distress of asphalt pavements,defined as the removal of stones from the pavement surface.To predict and assess raveling quantitatively,a cumulative damage model based on an energy dissipation approach has been developed at the meso level.To construct the model,a new test method,the pendulum impact test,was employed to determine the fracture energy of the stone-mastic-stone meso-unit,while digital image analysis and dynamic shear rheometer test were used to acquire the strain rate of specimens and the rheology property of mastic,respectively.Analysis of the model reveals that when the material properties remain constant,the cumulative damage is directly correlated with loading time,loading amplitude,and loading frequency.Specifically,damage increases with superimposed linear and cosine variations over time.A higher stress amplitude results in a more rapidly increasing rate of damage,while a lower load frequency leads to more severe damage within the same loading time.Moreover,an example of the application of the model has been presented,showing that the model can be utilized to estimate failure life due to raveling.The model is able to offer a theoretical foundation for the design and maintenance of anti-raveling asphalt pavements.展开更多
文摘A dissipative-based adaptive neural control scheme was developed for a class of nonlinear uncertain systems with unknown nonlinearities that might not be linearly parameterized. The major advantage of the present work was to relax the requirement of matching condition, i.e., the unknown nonlinearities appear on the same equation as the control input in a state-space representation, which was required in most of the available neural network controllers. By synthesizing a state-feedback neural controller to make the closed-loop system dissipative with respect to a quadratic supply rate, the developed control scheme guarantees that the L2-gain of controlled system was less than or equal to a prescribed level. And then, it is shown that the output tracking error is uniformly ultimate bounded. The design scheme is illustrated using a numerical simulation.
基金The authors gratefully acknowledge the financial supports by the National Natural Science Foundation of China(Grant No.51278203)the Natural Science Fund of Guangdong Province(No.2019A1515011965).
文摘Raveling is a common distress of asphalt pavements,defined as the removal of stones from the pavement surface.To predict and assess raveling quantitatively,a cumulative damage model based on an energy dissipation approach has been developed at the meso level.To construct the model,a new test method,the pendulum impact test,was employed to determine the fracture energy of the stone-mastic-stone meso-unit,while digital image analysis and dynamic shear rheometer test were used to acquire the strain rate of specimens and the rheology property of mastic,respectively.Analysis of the model reveals that when the material properties remain constant,the cumulative damage is directly correlated with loading time,loading amplitude,and loading frequency.Specifically,damage increases with superimposed linear and cosine variations over time.A higher stress amplitude results in a more rapidly increasing rate of damage,while a lower load frequency leads to more severe damage within the same loading time.Moreover,an example of the application of the model has been presented,showing that the model can be utilized to estimate failure life due to raveling.The model is able to offer a theoretical foundation for the design and maintenance of anti-raveling asphalt pavements.
