A GPC (generalized predictive control) law is developed to control the powerof a turbine, after transforming the nonlinear mathematical model of the power regulation systeminto a CARIMA(controlled auto-regressive inte...A GPC (generalized predictive control) law is developed to control the powerof a turbine, after transforming the nonlinear mathematical model of the power regulation systeminto a CARIMA(controlled auto-regressive integrated moving average) form. The effect of the newcontrol law is compared with a traditional PID (proportional, integral and differential) control lawby numerical simulation. The simulation results verify the effectiveness, the correctness and theadvantage of the new control scheme.展开更多
Due to the impact of source-load prediction power errors and uncertainties,the actual operation of the park will have a wide range of fluctuations compared with the expected state,resulting in its inability to achieve...Due to the impact of source-load prediction power errors and uncertainties,the actual operation of the park will have a wide range of fluctuations compared with the expected state,resulting in its inability to achieve the expected economy.This paper constructs an operating simulation model of the park power grid operation considering demand response and proposes a multi-time scale operating simulation method that combines day-ahead optimization and model predictive control(MPC).In the day-ahead stage,an operating simulation plan that comprehensively considers the user’s side comfort and operating costs is proposed with a long-term time scale of 15 min.In order to cope with power fluctuations of photovoltaic,wind turbine and conventional load,MPC is used to track and roll correct the day-ahead operating simulation plan in the intra-day stage to meet the actual operating operation status of the park.Finally,the validity and economy of the operating simulation strategy are verified through the analysis of arithmetic examples.展开更多
A constrained generalized predictive control （GPC） algorithm based on the T-S fuzzy model is presented for the nonlinear system. First, a Takagi-Sugeno （T-S） fuzzy model based on the fuzzy cluster algorithm and th...A constrained generalized predictive control （GPC） algorithm based on the T-S fuzzy model is presented for the nonlinear system. First, a Takagi-Sugeno （T-S） fuzzy model based on the fuzzy cluster algorithm and the orthogonalleast square method is constructed to approach the nonlinear system. Since its consequence is linear, it can divide the nonlinear system into a number of linear or nearly linear subsystems. For this T-S fuzzy model, a GPC algorithm with input constraints is presented. This strategy takes into account all the constraints of the control signal and its increment, and does not require the calculation of the Diophantine equations. So it needs only a small computer memory and the computational speed is high. The simulation results show a good performance for the nonlinear systems.展开更多
Cascade control is one of the most popular structures for process control as it is a special architecture for dealing with disturbances. However, the drawbacks of cascade control are obvious that primary controller an...Cascade control is one of the most popular structures for process control as it is a special architecture for dealing with disturbances. However, the drawbacks of cascade control are obvious that primary controller and secondary controller should be tuned together, which influences each other. In this paper, a new Adaptive Cascade Generalized Predictive Controller (ACGPC) is introduced. ACGPC is a method issued from GPC and the inner and outer controllers of a cascade system are replaced by one cascade generalized predictive controller, where both loops model are updated by Recursive Least Squares method. Compared with existing methods, the new method is simpler and yet more effective. It can be directly integrated into commercially available industrial auto-tuning systems. Some examples are given to illustrate the effectiveness and robustness of the proposed method.展开更多
Some papers on stochastic adaptive control schemes have established convergence algorithm using a least-squares parameters. With the popular application of GPC, global convergence has become a key problem in automatic...Some papers on stochastic adaptive control schemes have established convergence algorithm using a least-squares parameters. With the popular application of GPC, global convergence has become a key problem in automatic control theory. However, now global convergence of GPC has not been established for algorithms in computing a least squares iteration. A generalized model of adaptive generalized predictive control is presented. The global convergebce is also given on the basis of estimating the parameters of GPC by least squares algorithm.展开更多
Control of pH neutralization processes is challenging in the chemical process industry because of their inherent strong nonlinearity. In this paper, the model algorithmic control (MAC) strategy is extended to nonlinea...Control of pH neutralization processes is challenging in the chemical process industry because of their inherent strong nonlinearity. In this paper, the model algorithmic control (MAC) strategy is extended to nonlinear processes using Hammerstein model that consists of a static nonlinear polynomial function followed in series by a linear impulse response dynamic element. A new nonlinear Hammerstein MAC algorithm (named NLH-MAC) is presented in detail. The simulation control results of a pH neutralization process show that NLH-MAC gives better control performance than linear MAC and the commonly used industrial nonlinear propotional plus integral plus derivative (PID) controller. Further simulation experiment demonstrates that NLH-MAC not only gives good control response, but also possesses good stability and robustness even with large modeling errors.展开更多
In the semi-physical simulation of aeroengines,using the pneumatic pressure servo control technology to provide realistic pneumatic excitation to the sensors and electronic controller can improve the confidence of the...In the semi-physical simulation of aeroengines,using the pneumatic pressure servo control technology to provide realistic pneumatic excitation to the sensors and electronic controller can improve the confidence of the simulation and reduce the test cost and risk.However,the existing methods could not satisfy the precise simulation of large-amplitude and high-frequency pulsating pressure during aeroengine surge.In this paper,a pneumatic pressure control system with asymmetric groups of the High-Speed on–off Valve(HSV)is designed,and an Improved Nonlinear Model Predictive Control(INMPC)method is proposed.First,the volumetric flow characteristics of HSV are tested and analyzed with Pulse Width Modulation(PWM)signal input.Then,a simplified HSV model with the volume flow characteristic correction is developed.Based on these,an integrated model for the whole system is further established and used as the prediction model in INMPC.To improve the computational speed of the rolling optimization process,the mapping scheme from control signal to PWM duty cycle of HSVs and the objective function with exterior penalty function are designed.Finally,the random step,sinusoidal and real engine surge data are set as the reference pressure in multiple comparative experiments to verify the effectiveness of the pressure tracking system.展开更多
The fuzzy NN predictive control algorithm introduced in this paper uses fuzzy neural network to model the nonlinear MIMO process. Its training method that integrates LS and BP algorithm brings quick convergence. GPC a...The fuzzy NN predictive control algorithm introduced in this paper uses fuzzy neural network to model the nonlinear MIMO process. Its training method that integrates LS and BP algorithm brings quick convergence. GPC algorithm is used as the predictive component. The fuzzy neural network has six layers, including input layer, output layer and four hidden layers. An application to a MIMO nonlinear process(green liquor system of the recovery system in a pulp factory shows that this algorithm has better performance than normal PID algrithm.展开更多
In order to design an optimal controller for the thyristor controlled series capacitor （TCSC）, a novel TCSC control model is developed. In the model, the delay angle of thyristor valves is the input, and the inducto...In order to design an optimal controller for the thyristor controlled series capacitor （TCSC）, a novel TCSC control model is developed. In the model, the delay angle of thyristor valves is the input, and the inductor current is chosen as the output. Theoretical analysis and simulation studies show that TCSC is a non-linear system and its parameters vary with the operating point. In consideration of the special characteristics of the TCSC, an improved model algorithmic control （1MAC） scheme is proposed to control TCSC effectively. The good performance can be observed from simulation results when IMAC is applied to a series compensated radial system.展开更多
In oil drilling processes,sand production in the oil layer is a common issue,generally mitigated by means of sand control screens.To prevent or reduce the risk of damage of these screens and to improve the related ser...In oil drilling processes,sand production in the oil layer is a common issue,generally mitigated by means of sand control screens.To prevent or reduce the risk of damage of these screens and to improve the related service life,it is necessary to investigate the related erosion dynamics.In this study,a screen mesh model based on the flow field similarity theory is proposed to overcome the otherwise too complex geometric structure of this type of equipment.Such model is optimized using experimental data.The predicted results are in good agreement with the measured values,and the error is less than 15%.The results also show that the simplified geometric screen model and the optimized Zhang et al.erosion model have high reliability;therefore,they could effective be used to select underground screen meshes and improve the design of production process.展开更多
文摘A GPC (generalized predictive control) law is developed to control the powerof a turbine, after transforming the nonlinear mathematical model of the power regulation systeminto a CARIMA(controlled auto-regressive integrated moving average) form. The effect of the newcontrol law is compared with a traditional PID (proportional, integral and differential) control lawby numerical simulation. The simulation results verify the effectiveness, the correctness and theadvantage of the new control scheme.
基金supported by the Science and Technology Project of State Grid Shanxi Electric Power Research Institute:Research on Data-Driven New Power System Operation Simulation and Multi Agent Control Strategy(52053022000F).
文摘Due to the impact of source-load prediction power errors and uncertainties,the actual operation of the park will have a wide range of fluctuations compared with the expected state,resulting in its inability to achieve the expected economy.This paper constructs an operating simulation model of the park power grid operation considering demand response and proposes a multi-time scale operating simulation method that combines day-ahead optimization and model predictive control(MPC).In the day-ahead stage,an operating simulation plan that comprehensively considers the user’s side comfort and operating costs is proposed with a long-term time scale of 15 min.In order to cope with power fluctuations of photovoltaic,wind turbine and conventional load,MPC is used to track and roll correct the day-ahead operating simulation plan in the intra-day stage to meet the actual operating operation status of the park.Finally,the validity and economy of the operating simulation strategy are verified through the analysis of arithmetic examples.
基金supported by National Natural Science Foundation of China(61533013,61273144)Scientific Technology Research and Development Plan Project of Tangshan(13130298B)Scientific Technology Research and Development Plan Project of Hebei(z2014070)
基金This Project was supported by the National Natural Science Foundation of China (60374037 and 60574036)the Opening Project Foundation of National Lab of Industrial Control Technology (0708008).
文摘A constrained generalized predictive control （GPC） algorithm based on the T-S fuzzy model is presented for the nonlinear system. First, a Takagi-Sugeno （T-S） fuzzy model based on the fuzzy cluster algorithm and the orthogonalleast square method is constructed to approach the nonlinear system. Since its consequence is linear, it can divide the nonlinear system into a number of linear or nearly linear subsystems. For this T-S fuzzy model, a GPC algorithm with input constraints is presented. This strategy takes into account all the constraints of the control signal and its increment, and does not require the calculation of the Diophantine equations. So it needs only a small computer memory and the computational speed is high. The simulation results show a good performance for the nonlinear systems.
文摘Cascade control is one of the most popular structures for process control as it is a special architecture for dealing with disturbances. However, the drawbacks of cascade control are obvious that primary controller and secondary controller should be tuned together, which influences each other. In this paper, a new Adaptive Cascade Generalized Predictive Controller (ACGPC) is introduced. ACGPC is a method issued from GPC and the inner and outer controllers of a cascade system are replaced by one cascade generalized predictive controller, where both loops model are updated by Recursive Least Squares method. Compared with existing methods, the new method is simpler and yet more effective. It can be directly integrated into commercially available industrial auto-tuning systems. Some examples are given to illustrate the effectiveness and robustness of the proposed method.
基金Supported by the National Creative Research Groups Science Foundation of P.R. China （NCRGSFC： 60421002） and National High Technology Research and Development Program of China （863 Program） （2006AA04 Z182）
基金This project was supported by the National Natural Science Foundation of China (60174021) Tianjin Advanced School Science and Technology Development Foundation (01 - 20403) .
文摘Some papers on stochastic adaptive control schemes have established convergence algorithm using a least-squares parameters. With the popular application of GPC, global convergence has become a key problem in automatic control theory. However, now global convergence of GPC has not been established for algorithms in computing a least squares iteration. A generalized model of adaptive generalized predictive control is presented. The global convergebce is also given on the basis of estimating the parameters of GPC by least squares algorithm.
文摘Control of pH neutralization processes is challenging in the chemical process industry because of their inherent strong nonlinearity. In this paper, the model algorithmic control (MAC) strategy is extended to nonlinear processes using Hammerstein model that consists of a static nonlinear polynomial function followed in series by a linear impulse response dynamic element. A new nonlinear Hammerstein MAC algorithm (named NLH-MAC) is presented in detail. The simulation control results of a pH neutralization process show that NLH-MAC gives better control performance than linear MAC and the commonly used industrial nonlinear propotional plus integral plus derivative (PID) controller. Further simulation experiment demonstrates that NLH-MAC not only gives good control response, but also possesses good stability and robustness even with large modeling errors.
基金co-supported by the National Natural Science Foundation of China(No.51976089)the Natural Science Foundation of Fujian Province of China(No.2021J05113).
文摘In the semi-physical simulation of aeroengines,using the pneumatic pressure servo control technology to provide realistic pneumatic excitation to the sensors and electronic controller can improve the confidence of the simulation and reduce the test cost and risk.However,the existing methods could not satisfy the precise simulation of large-amplitude and high-frequency pulsating pressure during aeroengine surge.In this paper,a pneumatic pressure control system with asymmetric groups of the High-Speed on–off Valve(HSV)is designed,and an Improved Nonlinear Model Predictive Control(INMPC)method is proposed.First,the volumetric flow characteristics of HSV are tested and analyzed with Pulse Width Modulation(PWM)signal input.Then,a simplified HSV model with the volume flow characteristic correction is developed.Based on these,an integrated model for the whole system is further established and used as the prediction model in INMPC.To improve the computational speed of the rolling optimization process,the mapping scheme from control signal to PWM duty cycle of HSVs and the objective function with exterior penalty function are designed.Finally,the random step,sinusoidal and real engine surge data are set as the reference pressure in multiple comparative experiments to verify the effectiveness of the pressure tracking system.
文摘The fuzzy NN predictive control algorithm introduced in this paper uses fuzzy neural network to model the nonlinear MIMO process. Its training method that integrates LS and BP algorithm brings quick convergence. GPC algorithm is used as the predictive component. The fuzzy neural network has six layers, including input layer, output layer and four hidden layers. An application to a MIMO nonlinear process(green liquor system of the recovery system in a pulp factory shows that this algorithm has better performance than normal PID algrithm.
文摘In order to design an optimal controller for the thyristor controlled series capacitor （TCSC）, a novel TCSC control model is developed. In the model, the delay angle of thyristor valves is the input, and the inductor current is chosen as the output. Theoretical analysis and simulation studies show that TCSC is a non-linear system and its parameters vary with the operating point. In consideration of the special characteristics of the TCSC, an improved model algorithmic control （1MAC） scheme is proposed to control TCSC effectively. The good performance can be observed from simulation results when IMAC is applied to a series compensated radial system.
基金the Foundation of the National Natural Science Foundation of China(No.51974033)Educational Commission of Hubei Province of China(Q20191310,D20171305).
文摘In oil drilling processes,sand production in the oil layer is a common issue,generally mitigated by means of sand control screens.To prevent or reduce the risk of damage of these screens and to improve the related service life,it is necessary to investigate the related erosion dynamics.In this study,a screen mesh model based on the flow field similarity theory is proposed to overcome the otherwise too complex geometric structure of this type of equipment.Such model is optimized using experimental data.The predicted results are in good agreement with the measured values,and the error is less than 15%.The results also show that the simplified geometric screen model and the optimized Zhang et al.erosion model have high reliability;therefore,they could effective be used to select underground screen meshes and improve the design of production process.
