Jetron - APC algorithm and Software
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JETRON - APC Algorithm and Software
Zhuhai Jetron Huazi Technology Co.Ltd. is a joint venture between Jetron and Tsinghua University, which cooperates to develop industrial intelligent control software APC (JETRON Model-Based Predictive Control Algorithm), which is widely used in petrochemical, coal chemical, non-ferrous metal and building material industries. Jetron's model-based predictive control algorithm is an indispensable control technology for optimal operation of process industries, which can effectively enhance the anti-disturbance capability and process constraint handling capability of plant production, improve the stability of plant operation, reduce production fluctuations and human intervention intensity, and fully exploit the process and equipment capabilities of the plant by realizing "card edge operation". It can help customers to obtain the maximum economic benefits by realizing "card edge operation" to fully exploit the process and equipment capacity of the plant.
Feature
Nonlinear Predictive Control Technology
Modeling mechanisms that can adapt to the changing production environment (Expansion, Modification)
Online Model Switching Technology
Technology that enables online modification and tuning of controller model parameters
Dynamic Soft Sensing Technology
Soft sensing method that can adapt to changing operating conditions (such as raw material properties, large changes in load)
Integrate advanced control technologies such as process mechanism, intelligent control technology, expert operation knowledge, multi-variable predictive control technology and online optimization technology into one “intelligent” advanced control technology for a class of devices
An overall scheduling optimization solution based on the integration of advanced control, online device optimization, raw material blending and scheduling optimization, and product blending optimization
Fundamental
Scroll Optimization
★ Calculate the optimal control sequence once in each sampling period, and calculate it again in the next sampling period, and perform rolling execution over and over again, taking into account various uncertainties in the actual control process
★ The error of the model and the disturbance of the system are corrected by feedback through the measured value of the controlled variable, so that the system can reach the actual optimum.
Model Estimation
★ Use the model to estimate the motion and error of the controlled object in the future, and use it as the basis for determining the current control effect
★ Adapt the control strategy to the storage, causality and hysteresis of the controlled object, and obtain a better control effect
Feedback correction
★ Use measurable information to correct the estimated value at each sampling time to suppress errors caused by model mismatch and interference
★ Using the revised estimated value as the basis for calculating the optimal control, the robustness of the control system is significantly improved
Cases
Contact Us
Building 6, Ningxing Jiali Plaza, No. 185 Mingxin Road, Yinzhou District, Ningbo City
Tel:( 86-574 ) 87861201
Fax:( 86-574 ) 87861200
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