Explicit Indirect Predictive Control Algorithm in the Application of AWC Control

2014 ◽  
Vol 926-930 ◽  
pp. 1344-1347
Author(s):  
Fang Chen Yin ◽  
Geng Sheng Ma ◽  
Ya Feng Ji ◽  
Zhong Ping Li ◽  
Dian Hua Zhang
Keyword(s):  
Predictive Control ◽  
Delay Time ◽  
Control Algorithm ◽  
Continuous Mill ◽  
Control Performance ◽  
Hot Strip ◽  
Parameter Variations ◽  
Feedback Correction ◽  
Rolling Optimization ◽  
Pure Delay

Using the characteristics of prediction model, rolling optimization and feedback correction, a AWC system based on explicit indirect predictive control was designed, and its control performance was simulated based on a hot strip continuous mill. The results show that explicit indirect predictive control achieves better control effects than the normal PID on response time and steady precision with matching model; when model mismatching is caused by inaccuracy of plastic coefficient and pure delay time, the normal PID is overshot or even oscillation, but the control performance of the explicit indirect predictive control is not influenced by model parameter variations [1].

Fuzzy Adaptive Direct Generalized Predictive Control Algorithm in the Application of AWC Control

2014 ◽  
Vol 945-949 ◽  
pp. 2529-2532
Author(s):  
Fang Chen Yin ◽  
Geng Sheng Ma ◽  
Ya Feng Ji ◽  
Jia Xue Yu ◽  
De Hao Gu ◽  
...  
Keyword(s):  
Predictive Control ◽  
Generalized Predictive Control ◽  
Continuous Mill ◽  
Control Performance ◽  
Hot Strip ◽  
Predictive Controller ◽  
Feedback Correction ◽  
Rolling Optimization ◽  
Pure Delay ◽  
Fuzzy Adaptive

Using the characteristics of prediction model, rolling optimization and feedback correction, a AWC system based on generalized predictive control was designed, and its control performance was simulated based on a hot strip continuous mill. The results show that generalized predictive controller achieves better control effects than the normal PID on response time and steady precision with matching model; when model mismatching is caused by inaccuracy of plastic coefficient and pure delay time, the normal PID is overshot or even oscillation, but the control performance of the generalized predictive controller is not influenced by model parameter variations .

Analysis for Predictive Control Algorithm in District Heating

2012 ◽  
Vol 562-564 ◽  
pp. 1738-1742
Author(s):  
Tao Liang ◽  
Amei Guo ◽  
Hai Yan Ren
Keyword(s):  
Predictive Control ◽  
Control Algorithm ◽  
Closed Loop ◽  
Large Time ◽  
Algorithm Design ◽  
District Heating ◽  
Pole Placement ◽  
Central Heating ◽  
Feedback Correction ◽  
Placement Algorithm

Due to its characteristics of large time delay and large inertia, central heating pipe networks suits to be controlled by predictive control algorithm. In predictive control systems, adjustable parameters are immerged into the closed-loop polynomial and the explicit relationships are difficult to be found, which make the algorithm design difficult. In this paper, the closed-loop characteristics of multi-horizon predictive control strategy with feedback correction is analyzed, which shows that it is equivalent to a certain kind of pole-placement algorithm. This conclusion demonstrates the performance design of state-feedback predictive control easier to be achieved.

The Design and Simulation of Predictive Control Algorithm Achieved by the DCS Algorithm Module Combination

2011 ◽  
Vol 130-134 ◽  
pp. 175-178
Author(s):  
Qian Qian Quan
Keyword(s):  
Predictive Control ◽  
Control Algorithm ◽  
Design Method ◽  
Parameter Tuning ◽  
Control Software ◽  
Complex Objects ◽  
Software Module ◽  
Tuning Method ◽  
Complex Process ◽  
Pure Delay

This paper proposes a design method and parameter tuning method for how only using the DCS configuration control software module to combine and achieve generalized predictive control algorithm in a complicated controlled plant case. In order to show the effectiveness of the control algorithm using the DCS layer control software module to achieve model predictive, two types of complex objects are considered as example to do simulation : non-minimum phase process and the complex process with recycling and pure delay. The simulation results show that the proposed control algorithm can provide similar control performance of GPC.

Research of the Industrial Furnace Temperature Control Based on DMC Algorithm

2014 ◽  
Vol 556-562 ◽  
pp. 2240-2243
Author(s):  
Zhi Yong Meng ◽  
Chen Meng Sui ◽  
Lei Liu
Keyword(s):  
Prediction Model ◽  
Temperature Measurement ◽  
Temperature Control ◽  
Control Algorithm ◽  
Industrial Furnace ◽  
Furnace Temperature ◽  
Feedback Correction ◽  
Rolling Optimization

By introducing the existing lack of industrial temperature control algorithm is applied, leads to the advantage of DMC algorithm industrial furnace temperature control, the next from the prediction model, rolling optimization, feedback correction of the three aspects of the principle of DMC algorithm is fully explained, on this basis, the preparation of Matlab procedures, simulation of the DMC algorithm in industrial furnace temperature control, thus indicating DMC algorithm in the field of industrial temperature measurement is a method should be promoted.

scholarly journals Research on Intelligent Predictive AGC of a Thermal Power Unit Based on Control Performance Standards

Energies ◽  
2019 ◽  
Vol 12 (21) ◽  
pp. 4073
Author(s):  
Daogang Peng ◽  
Yue Xu ◽  
Huirong Zhao
Keyword(s):  
Neural Network ◽  
Predictive Control ◽  
Optimization Model ◽  
Power Grid ◽  
Thermal Power ◽  
Automatic Generation ◽  
Performance Standard ◽  
Control Performance ◽  
Predictive Controller ◽  
Rolling Optimization

In order to satisfy the growing demands of control performance and operation efficiency in the automatic generation control (AGC) system of a grid, a novel, intelligent predictive controller, combined with predictive control and neural network ideas, is proposed and applied to the AGC systems of thermal power units. This paper proposes a Bayesian neural network identification model for typical ultra-supercritical thermal power units, which was found to be accurate and can be used as a simulation model. Based on the model, this paper develops an intelligent predictive control for the AGC of thermal power units, which improves unit load operation and constitutes a novel, closed-loop AGC structure based on online control performance standard (CPS) evaluations. Intelligent predictive control is mainly improved because the neural network rolling optimization model replaces the traditional rolling optimization model in the rolling optimization module. The simulation results indicate that the intelligent predictive controller developed in the two-area interconnected power grid under CPS can, on the one hand, improve the load tracking performance of AGC thermal power units, and, on the other hand, the controller has strong robustness. Whether the system parameters change considerably or the AGC has different grid disturbances, the new type of the loop AGC system can still sufficiently meet the control requirements of the power grid.

scholarly journals A Predictive Control Model for Master Slave Robotic Manipulator with RBF Neural Network

2021 ◽  
Vol 15 ◽  
pp. 617-622
Author(s):  
Youjian Lei
Keyword(s):  
Predictive Control ◽  
Trajectory Tracking ◽  
Control Algorithm ◽  
Control Method ◽  
Sliding Mode ◽  
Rbf Neural Network ◽  
Robotic Manipulator ◽  
Practical Significance ◽  
The Difference ◽  
Rolling Optimization

In recent years, manipulator control has been widely concerned, and its uncertainty is one of the focuses. As we all know, the manipulator is a MIMO nonlinear system, which has the characteristics of severe variable coupling, large time-varying amplitude of parameters and high degree of nonlinearity. Therefore, a lot of uncertain factors must be considered when designing the control algorithm of manipulator system. The predictive control algorithm adopts online rolling optimization, and in the process of optimization, feedback correction is carried out by the difference between the actual output and the reference output. It can iterate the predictive model and suppress the influence of some uncertain disturbances to a certain extent. Therefore, the design of predictive controller for robot is not only of theoretical significance, but also of great practical significance. The trajectory tracking problem is proposed in this paper, and a predictive control method for master slave robotic manipulator with sliding mode controller is designed. In addition, when external disturbances occurred, the approximation errors are compensated by the proposed control method. Finally, The results demonstrate that the stability of the controllers can be improved for the trajectory tracking errors.

Coke Oven Flue Temperature Control Based on Improved Implicit Generalized Predictive Control

2018 ◽  
Vol 22 (2) ◽  
pp. 203-213 ◽  
Author(s):  
Zhongda Tian ◽  
◽  
Shujiang Li ◽  
Yanhong Wang
Keyword(s):  
Predictive Control ◽  
Control Algorithm ◽  
Control Method ◽  
Good Control ◽  
Coke Oven ◽  
Coefficient Matrix ◽  
Generalized Predictive Control ◽  
Heating Process ◽  
Control Performance ◽  
Flue Temperature

The flue temperature of coke oven is an important factor that guarantees the coke yield, the coke quality and the energy consumption of coking production. The heating process of coke oven is an object with multi control variables, nonlinear and large lag. The traditional PID control algorithm cannot further improve the control performance of the coke oven system. An improved implicit generalized predictive control algorithm with better control performance is proposed in this paper. Through inputting control increment value constrained by soft coefficient matrix, the calculation of matrix inversion is avoided. Soft coefficient matrix can reduce the computation time and ensure the rapidity of the system. At the same time, the input weight control law with smoothing filter is used to suppress the overshoot of the system output. Simulation results show that the proposed control method in this paper has the good control performance with faster computation speed. The proposed control method solves the problem of time variation and disturbance of coke oven system. The control algorithm of the coke oven flue temperature in this paper is effective.

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