Polynomial-time randomized algorithms were constructed to approximately solve optimal robust performance controller design problems in probabilistic sense and the rigorous mathematical justification of the approach wa...Polynomial-time randomized algorithms were constructed to approximately solve optimal robust performance controller design problems in probabilistic sense and the rigorous mathematical justification of the approach was given. The randomized algorithms here were based on a property from statistical learning theory known as (uniform) convergence of empirical means (UCEM). It is argued that in order to assess the performance of a controller as the plant varies over a pre-specified family, it is better to use the average performance of the controller as the objective function to be optimized, rather than its worst-case performance. The approach is illustrated to be efficient through an example.展开更多
During the hot rolling process,the performance of most control systems gradually degrades due to equipment aging and changing process conditions.However,existing gauge-looper-tension control method remain restricted b...During the hot rolling process,the performance of most control systems gradually degrades due to equipment aging and changing process conditions.However,existing gauge-looper-tension control method remain restricted by a lack of intelligent parameter maintenance strategies.To address this challenge and enhance the smart manufacturing capabilities of strip hot rolling,based on the digital twin method,this paper proposes a data-driven optimized control method for the gauge-looper-tension system of strip hot rolling.First,a hot rolling process model is constructed based on a digital twin method to serve as an evaluation and optimization platform.Subsequently,relevant data are collected to calculate the Hurst index for identifying the performance of the controller during the rolling process.Additionally,for controllers with poor Hurst index values,the crayfish optimization algorithm is employed for adjusting controller parameters to maximize the Hurst index.Experimental results demonstrate that the evaluation method effectively recognized the control state of gauge-looper-tension system and the optimization method successfully enhances the performance of the control system.Therefore,based on the digital twin platform,the proposed method can effectively maintain performance-degraded control systems.展开更多
文摘Polynomial-time randomized algorithms were constructed to approximately solve optimal robust performance controller design problems in probabilistic sense and the rigorous mathematical justification of the approach was given. The randomized algorithms here were based on a property from statistical learning theory known as (uniform) convergence of empirical means (UCEM). It is argued that in order to assess the performance of a controller as the plant varies over a pre-specified family, it is better to use the average performance of the controller as the objective function to be optimized, rather than its worst-case performance. The approach is illustrated to be efficient through an example.
基金supported by the National Natural Science Foundation of China[grant numbers U21A20117,52074085]the Fundamental Research Funds for the Central Universities[grant number N2004010]the LiaoNing Applied Basic Research Program Project[grant numbers 2022JH24/10200013].
文摘During the hot rolling process,the performance of most control systems gradually degrades due to equipment aging and changing process conditions.However,existing gauge-looper-tension control method remain restricted by a lack of intelligent parameter maintenance strategies.To address this challenge and enhance the smart manufacturing capabilities of strip hot rolling,based on the digital twin method,this paper proposes a data-driven optimized control method for the gauge-looper-tension system of strip hot rolling.First,a hot rolling process model is constructed based on a digital twin method to serve as an evaluation and optimization platform.Subsequently,relevant data are collected to calculate the Hurst index for identifying the performance of the controller during the rolling process.Additionally,for controllers with poor Hurst index values,the crayfish optimization algorithm is employed for adjusting controller parameters to maximize the Hurst index.Experimental results demonstrate that the evaluation method effectively recognized the control state of gauge-looper-tension system and the optimization method successfully enhances the performance of the control system.Therefore,based on the digital twin platform,the proposed method can effectively maintain performance-degraded control systems.
