We first discuss the relationship between the optimal track maintenance scheduling model and an efficient detection method for abnormal track irregularities given by the longitudinal level irregularity displaceme...We first discuss the relationship between the optimal track maintenance scheduling model and an efficient detection method for abnormal track irregularities given by the longitudinal level irregularity displacement (LLID). The results of applying the cluster analysis technique to the sampling data showed that maintenance operation is required for approximately 10% of the total lots, and these lots were further classified into three groups according to the degree of maintenance need. To analyze the background factors for detecting abnormal LLID lots, a principal component analysis was performed;the results showed that the first principal component represents LLIDs from the viewpoints of the rail structure, equipment, and operating conditions. Binomial and ordinal logit regression models (LRMs) were used to quantitatively investigate the determinants of abnormal LLIDs. Binomial LRM was used to characterize the abnormal LLIDs, whereas ordinal LRM was used to distinguish the degree of influence of factors that are considered to have a significant impact on LLIDs.展开更多
Systems with large operating regions and non-zero state target tracking have limited the industrial application of robust model predictive control (RMPC) with synthetic action. To overcome the problem, this paper pres...Systems with large operating regions and non-zero state target tracking have limited the industrial application of robust model predictive control (RMPC) with synthetic action. To overcome the problem, this paper presents a novel formulation of synthesizing scheduled RMPC for linear time varying (LTV) systems. Off-line, we compute the matrix that transforms target output into steady state first. Then a set of stabilizing state feedback laws which are corresponding to a set of estimated regions of stability covering the desired operating region are provided. On-line, these control laws are implemented as a single scheduled state feedback model predictive control (MPC) which switches between the set of local controllers and achieve the desired target at last. Finally, the algorithm is illustrated with an example.展开更多
An actual control demand of rotary kiln is taken as background. By analyzing and improving approach of MPC （synthesizing model predictive control）, an effective strategy which applies complex S-MPC in actual industr...An actual control demand of rotary kiln is taken as background. By analyzing and improving approach of MPC （synthesizing model predictive control）, an effective strategy which applies complex S-MPC in actual industrial process is designed. Firstly, after analyzing the main components technology and calcination reaction mechanism in detail, the calcining belt state-space model of rotary kiln is built using PO-Moesp （past-output multivariable output error state space model identification） method. Then, calcining belt temperature predictive control system is de signed. The control system combines time-delay gain scheduled, output-tracking, recursive subspace adaptive and other methods, and forms the off-line/on-line predictive controller of rotary kiln. At last, MATLAB is applied for simulation, experiments run in constant value tracking and servo tracking situation. Simulation results show its ef- fectiveness and feasibility.展开更多
文摘We first discuss the relationship between the optimal track maintenance scheduling model and an efficient detection method for abnormal track irregularities given by the longitudinal level irregularity displacement (LLID). The results of applying the cluster analysis technique to the sampling data showed that maintenance operation is required for approximately 10% of the total lots, and these lots were further classified into three groups according to the degree of maintenance need. To analyze the background factors for detecting abnormal LLID lots, a principal component analysis was performed;the results showed that the first principal component represents LLIDs from the viewpoints of the rail structure, equipment, and operating conditions. Binomial and ordinal logit regression models (LRMs) were used to quantitatively investigate the determinants of abnormal LLIDs. Binomial LRM was used to characterize the abnormal LLIDs, whereas ordinal LRM was used to distinguish the degree of influence of factors that are considered to have a significant impact on LLIDs.
文摘Systems with large operating regions and non-zero state target tracking have limited the industrial application of robust model predictive control (RMPC) with synthetic action. To overcome the problem, this paper presents a novel formulation of synthesizing scheduled RMPC for linear time varying (LTV) systems. Off-line, we compute the matrix that transforms target output into steady state first. Then a set of stabilizing state feedback laws which are corresponding to a set of estimated regions of stability covering the desired operating region are provided. On-line, these control laws are implemented as a single scheduled state feedback model predictive control (MPC) which switches between the set of local controllers and achieve the desired target at last. Finally, the algorithm is illustrated with an example.
基金Item Sponsored by National Natural Science Foundation of China(61034005)
文摘An actual control demand of rotary kiln is taken as background. By analyzing and improving approach of MPC （synthesizing model predictive control）, an effective strategy which applies complex S-MPC in actual industrial process is designed. Firstly, after analyzing the main components technology and calcination reaction mechanism in detail, the calcining belt state-space model of rotary kiln is built using PO-Moesp （past-output multivariable output error state space model identification） method. Then, calcining belt temperature predictive control system is de signed. The control system combines time-delay gain scheduled, output-tracking, recursive subspace adaptive and other methods, and forms the off-line/on-line predictive controller of rotary kiln. At last, MATLAB is applied for simulation, experiments run in constant value tracking and servo tracking situation. Simulation results show its ef- fectiveness and feasibility.
