Based on the two-dimensional （2D） system theory, an integrated predictive iterative learning control （2D-IPILC） strategy for batch processes is presented. First, the output response and the error transition model ...Based on the two-dimensional （2D） system theory, an integrated predictive iterative learning control （2D-IPILC） strategy for batch processes is presented. First, the output response and the error transition model predictions along the batch index can be calculated analytically due to the 2D Roesser model of the batch process. Then, an integrated framework of combining iterative learning control （ILC） and model predictive control （MPC） is formed reasonably. The output of feedforward ILC is estimated on the basis of the predefined process 2D model. By min- imizing a quadratic objective function, the feedback MPC is introduced to obtain better control performance for tracking problem of batch processes. Simulations on a typical batch reactor demonstrate that the satisfactory tracking performance as well as faster convergence speed can be achieved than traditional proportion type （P- t-we） ILC despite the model error and disturbances.展开更多
This paper focuses on resolving the identification problem of a neuro-fuzzy model(NFM) applied in batch processes. A hybrid learning algorithm is introduced to identify the proposed NFM with the idea of auxiliary erro...This paper focuses on resolving the identification problem of a neuro-fuzzy model(NFM) applied in batch processes. A hybrid learning algorithm is introduced to identify the proposed NFM with the idea of auxiliary error model and the identification principle based on the probability density function(PDF). The main contribution is that the NFM parameter updating approach is transformed into the shape control for the PDF of modeling error. More specifically, a virtual adaptive control system is constructed with the aid of the auxiliary error model and then the PDF shape control idea is used to tune NFM parameters so that the PDF of modeling error is controlled to follow a targeted PDF, which is in Gaussian or uniform distribution. Examples are used to validate the applicability of the proposed method and comparisons are made with the minimum mean square error based approaches.展开更多
This paper investigates the finite-time quasi-synchronization of two nonidentical Lur'e systems with parameter mismatches by using intermittent control. Based on Lyapunov stability theory and some differential ine...This paper investigates the finite-time quasi-synchronization of two nonidentical Lur'e systems with parameter mismatches by using intermittent control. Based on Lyapunov stability theory and some differential inequality techniques, sufficient conditions for finite-time quasi-synchronization are derived and the explicit expression of error level is obtained. Meanwhile, a numerical simulation is given to illustrate the effectiveness of the theoretical results.展开更多
An advanced control concept, Predictive Functional Control （PFC）, is applied for temperature control of a bench-scaled batch reactor equipped with monofluid heating/cooling system. First principles process models ar...An advanced control concept, Predictive Functional Control （PFC）, is applied for temperature control of a bench-scaled batch reactor equipped with monofluid heating/cooling system. First principles process models are developed. Based on achieved models, significant process variables, which are difficult or impossible to measure online, are estimated from easily measured variables, and cascade PFC control strategy has been projected and implemented in Matlab RI 4. The dynamics of individual subunits is explicitly taken into consideration by internal model in the control algorithms, and model uncertainty, various process disturbances are compensated by modifi- cation of internal model. The experimental results present an excellent capability of tracking the set point, and the success of PFC technique as a process control paradigm is illustratively demonstrated.展开更多
基金Supported in part by the State Key Development Program for Basic Research of China(2012CB720505)the National Natural Science Foundation of China(61174105,60874049)
文摘Based on the two-dimensional （2D） system theory, an integrated predictive iterative learning control （2D-IPILC） strategy for batch processes is presented. First, the output response and the error transition model predictions along the batch index can be calculated analytically due to the 2D Roesser model of the batch process. Then, an integrated framework of combining iterative learning control （ILC） and model predictive control （MPC） is formed reasonably. The output of feedforward ILC is estimated on the basis of the predefined process 2D model. By min- imizing a quadratic objective function, the feedback MPC is introduced to obtain better control performance for tracking problem of batch processes. Simulations on a typical batch reactor demonstrate that the satisfactory tracking performance as well as faster convergence speed can be achieved than traditional proportion type （P- t-we） ILC despite the model error and disturbances.
基金Supported by the National Natural Science Foundation of China(61374044)Shanghai Science Technology Commission(12510709400)+1 种基金Shanghai Municipal Education Commission(14ZZ088)Shanghai Talent Development Plan
文摘This paper focuses on resolving the identification problem of a neuro-fuzzy model(NFM) applied in batch processes. A hybrid learning algorithm is introduced to identify the proposed NFM with the idea of auxiliary error model and the identification principle based on the probability density function(PDF). The main contribution is that the NFM parameter updating approach is transformed into the shape control for the PDF of modeling error. More specifically, a virtual adaptive control system is constructed with the aid of the auxiliary error model and then the PDF shape control idea is used to tune NFM parameters so that the PDF of modeling error is controlled to follow a targeted PDF, which is in Gaussian or uniform distribution. Examples are used to validate the applicability of the proposed method and comparisons are made with the minimum mean square error based approaches.
基金Supported by National Natural Science Foundation of China under Grant No.11171216
文摘This paper investigates the finite-time quasi-synchronization of two nonidentical Lur'e systems with parameter mismatches by using intermittent control. Based on Lyapunov stability theory and some differential inequality techniques, sufficient conditions for finite-time quasi-synchronization are derived and the explicit expression of error level is obtained. Meanwhile, a numerical simulation is given to illustrate the effectiveness of the theoretical results.
基金Financially supported by the Doctoral Fund of Ministry of Education of China(No.20126101120015)Natural Science Foundation of Education Department of Shaanxi Provincial Government(2013JK0619)
文摘An advanced control concept, Predictive Functional Control （PFC）, is applied for temperature control of a bench-scaled batch reactor equipped with monofluid heating/cooling system. First principles process models are developed. Based on achieved models, significant process variables, which are difficult or impossible to measure online, are estimated from easily measured variables, and cascade PFC control strategy has been projected and implemented in Matlab RI 4. The dynamics of individual subunits is explicitly taken into consideration by internal model in the control algorithms, and model uncertainty, various process disturbances are compensated by modifi- cation of internal model. The experimental results present an excellent capability of tracking the set point, and the success of PFC technique as a process control paradigm is illustratively demonstrated.
