The Technology to Embed the Predictive Control Algorithm into Configuration Control Software at the DCS Level

2012 ◽  
Vol 433-440 ◽  
pp. 5556-5563
Author(s):  
Qian Qian Quan
Keyword(s):  
Predictive Control ◽  
Control Algorithm ◽  
Thermal Power ◽  
Control Software ◽  
Nonlinear Gain ◽  
Scheme Design ◽  
Complex Process ◽  
Control Scheme ◽  
Scheme Analysis ◽  
Configuration Control

The development work and proposes the technique to embed the predictive control algorithm into configuration control software at the DCS level. The thesis presents the technique and its application scheme to control CFBB super-heated steam temperature in a thermal power plant. The control scheme includes that the description of controlled plant characters, conventional control scheme analysis and improved control scheme design. It integrates feed-back and feed-forward DMC with DMC-PID cascade control and nonlinear gain-scheduling compensation for actuator. Satisfactory industrial application results show that such a control scheme has enhanced robustness to the complex process, and better control performance has been obtained.

scholarly journals Stair-like Multivariable Generalized Predictive Control of Pulverizing System in Thermal Power Plants

2018 ◽  
Vol 3 (1) ◽  
pp. 21
Author(s):  
Jiansheng ZHANG ◽  
Gang ZhANG ◽  
Yaokui GAO ◽  
Yong HU
Keyword(s):  
Predictive Control ◽  
Control Algorithm ◽  
Power Plants ◽  
Thermal Power ◽  
Engineering Application ◽  
Generalized Predictive Control ◽  
Practical Application ◽  
Efficient Utilization ◽  
Control Scheme ◽  
Control Schemes

Pulverizing system is an important part in the clean and efficient utilization of coal in thermal power plant, and the optimal control of the system is an important way to achieve this goal. This paper presents a stair-like multivariable generalized predictive control scheme for a pulverizing system. This control scheme focuses on the problem of predictive control algorithm in practical application, and integrates the feedforward experience in traditional control schemes of pulverizing system. Simulation results showed that the scheme are able to realize the decoupling control of the pulverizing system, avoid the problem of matrix inversion, reduce the amount of calculation, and has certain engineering application value.

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 on Accurate Modeling and Control for Pneumatic Electric Braking System of Commercial Vehicle Based on Multi-Dynamic Parameters Measurement

2020 ◽  
Author(s):  
Yongtao Zhao ◽  
Yiyong Yang ◽  
Xiuheng Wu ◽  
Xingjun Tao
Keyword(s):  
Dynamic Response ◽  
Real Time ◽  
Predictive Control ◽  
Control Algorithm ◽  
Control Algorithms ◽  
Dynamic Parameters ◽  
Braking System ◽  
Control Scheme ◽  
Braking Force ◽  
Electric Braking

Abstract Accurate pressure control and fast dynamic response are vital to the pneumatic electric braking system (PEBS) for that commercial vehicles require higher regulation precision of braking force on four wheels when braking force distribution is carried out under some conditions. Due to the lagging information acquisition, most feedback-based control algorithms are difficult to further improve the dynamic response of PEBS. Meanwhile, feedforward-based control algorithms like predictive control perform well in improving dynamic performance. but because of the large amount of computation and complexity of this kind of control algorithm, it cannot be applied in real-time on single-chip microcomputer, and it is still in the stage of theoretical research at present. To address this issue and for the sake of engineering reliability, this article presents a logic threshold control scheme combining analogous model predictive control (AMPC) and proportional control. In addition, an experimental device for real-time measuring PEBS multi-dynamic parameters is built. After correcting the key parameters, the precise model is determined and the influence of switching solenoid valve on its dynamic response characteristics is studied. For the control scheme, numerical and physical validation are executed to demonstrate the feasibility of the strategy and for the performance of the controller design. The experimental results show that the dynamic model of PEBS can accurately reflect its pressure characteristics. Furthermore, under different air source pressures, the designed controller can stably control the pressure output of PEBS and ensure that the error is within 8KPa. Compared with the traditional control algorithm, the rapidity is improved by 32.5%.

scholarly journals Performance Analysis of Reheat Steam Temperature Control System of Thermal Power Unit Based on Constrained Predictive Control

Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-12 ◽  
Author(s):  
Xiaoli Li ◽  
Jian Liu ◽  
Kang Wang ◽  
Fuqiang Wang ◽  
Yang Li
Keyword(s):  
Control System ◽  
Steady State ◽  
Power Unit ◽  
Predictive Control ◽  
Temperature Control ◽  
Control Algorithm ◽  
Thermal Power ◽  
Temperature Control System ◽  
Steam Temperature ◽  
Reheat Steam

The reheat steam temperature control system of thermal power unit is a complex control object with time-varying parameters and large delay. In order to achieve precise control of reheat steam temperature, the performance of the reheat temperature control system is analyzed according to the data that are obtained based on the constrained predictive control algorithm. Firstly, the process and mathematical model of reheat steam temperature control system are introduced. Then the principle of constrained predictive control algorithm is analyzed. Finally, the steady-state values of control quantities of reheat steam temperature control system under different conditions are given by MATLAB simulation, and, by analyzing the steady-state values and steady-state time of the input and output of the system, the reference values and the regulating law of the control quantities and the specific constraint range of the control quantities of the system are given, which can provide reference data and theoretical basis for the field adjustment of the reheat steam temperature control system in power plant and improve the safety and effectiveness of the system.

Analysis the Effect of Undesirable Factors on Stability of Model Predictive Controller

2008 ◽  
Author(s):  
Shadi Ansarpanahi ◽  
Samsul Bahari Mohd Noor
Keyword(s):  
Predictive Control ◽  
Time Delays ◽  
Control Algorithm ◽  
Computer Control ◽  
Phase System ◽  
Control Scheme ◽  
Predictive Controller ◽  
Noise Error ◽  
The Stability ◽  
Drive Model

MPC also known as moving or receding horizon control, is a feedback control scheme that has originated in industry as a real-time computer control algorithm to solve linear and nonlinear multi-variable problems that have constraints and time delays. Since disturbances can drive model predictive control into non-convexity and instability this problem has attracted many researchers. The stability studies in this paper are illustrated in presence of colored noise, error in delay estimation, unstable and non-minimum phase system by means of numerical example. The simulation is carried out using an example, which is the main contribution of the paper.

Levitation System Controller Design Based on the Implicit General Predictive Control Algorithm

2013 ◽  
Vol 444-445 ◽  
pp. 806-811
Author(s):  
Yu Yin Wang ◽  
Jie Li
Keyword(s):  
Predictive Control ◽  
Control Algorithm ◽  
Controller Design ◽  
Linear Character ◽  
Maglev System ◽  
Control Scheme ◽  
Levitation System ◽  
The Stability ◽  
General Predictive Control ◽  
System Controller

The levitation control system is a key technique of the maglev system. Due to the strong non-linear character of the magnetic force, as well as the model uncertainties and external interferences of the maglev system, the Implicit General Predictive Control algorithm, which adjusts the parameters of the control scheme by using the input and output data, is adopted in this article. Taking the single electro-magnet levitation system as the research object, this algorithm not only guarantees the stability of the system, but also suppresses the vibration caused by the flexibility of the track. The advantages of this algorithm include: the superior control capacity, roll over optimization and little dependence on model. The simulation approves the validity of this method.

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