scholarly journals Automatic control system of boiler thermal energy in thermal power plant based on artificial intelligence technology

2021 ◽  
Vol 25 (4 Part B) ◽  
pp. 3141-3148
Author(s):  
Yu Zeng ◽  
Fuchao Cheng
Keyword(s):  
Artificial Intelligence ◽  
Automatic Control ◽  
Control Method ◽  
Thermal Power ◽  
Influence Factors ◽  
Regulation System ◽  
Proportional Integral Derivative ◽  
Monitoring Method ◽  
Proportional Integral ◽  
Artificial Intelligence Technology

Thermal processes tend to have large inertia and hysteresis, non-linearity, and slow time-varying. Therefore, the fixed-parameter proportional integral derivative conventional regulation system cannot meet the higher and higher control requirements in production. Based on this research background, the paper proposes an automatic control method for thermal boiler steam based on artificial intelligence technology. Through the real-time monitoring of the boiler, the state monitoring method is used to estimate the influence factors of the boiler, and the estimated error output is artificially supplemented to realize the accurate control of the boiler. After being put on the market, it is found that the control method proposed in the article can overcome the randomness and inertia of the temperature and accurately realize the temperature control of the boiler. Moreover, compared with the traditional proportional integral derivative control, this method is more effective.

A new control method based on fuzzy controller, time delay estimation, deep learning, and non-dominated sorting genetic algorithm-III for powertrain mount system

2019 ◽  
Vol 26 (13-14) ◽  
pp. 1187-1198 ◽  
Author(s):  
Li-Xin Guo ◽  
Dinh-Nam Dao
Keyword(s):  
Genetic Algorithm ◽  
Fuzzy Logic ◽  
Deep Learning ◽  
Fuzzy Logic Controller ◽  
Control Method ◽  
Time Delay Estimation ◽  
Delay Estimation ◽  
Proportional Integral Derivative ◽  
Proportional Integral Derivative Controller ◽  
Proportional Integral

This article presents a new control method based on fuzzy controller, time delay estimation, deep learning, and non-dominated sorting genetic algorithm-III for the nonlinear active mount systems. The proposed method, intelligent adapter fractions proportional–integral–derivative controller, is a smart combination of the time delay estimation control and intelligent fractions proportional–integral–derivative with adaptive control parameters following the speed range of engine rotation via the deep neural network with the optimal non-dominated sorting genetic algorithm-III deep learning algorithm. Besides, we proposed optimal fuzzy logic controller with optimal parameters via particle swarm optimization algorithm to control reciprocal compensation to eliminate errors for intelligent adapter fractions proportional–integral–derivative controller. The control objective is to deal with the classical conflict between minimizing engine vibration impacts on the chassis to increase the ride comfort and keeping the dynamic wheel load small to ensure the ride safety. The results of this control method are compared with that of traditional proportional–integral–derivative controller systems, optimal proportional–integral–derivative controller parameter adjustment using genetic algorithms, linear–quadratic regulator control algorithms, and passive drive system mounts. The results are tested in both time and frequency domains to verify the success of the proposed optimal fuzzy logic controller–intelligent adapter fractions proportional–integral–derivative control system. The results show that the proposed optimal fuzzy logic controller–intelligent adapter fractions proportional–integral–derivative control system of the active engine mount system gives very good results in comfort and softness when riding compared with other controllers.

scholarly journals Special aspects of strain localization during thermal power processing

2021 ◽  
pp. 26-34
Author(s):  
D. A. Rastorguev ◽  
◽  
K. O. Semenov ◽  
Keyword(s):  
Plastic Deformation ◽  
Plastic Flow ◽  
Flow Curve ◽  
Strain Distribution ◽  
Control Method ◽  
Thermal Power ◽  
Main Task ◽  
Workpiece Material ◽  
Monitoring Method ◽  
Simultaneous Application

The paper considers the issues of ensuring the uniformity of strain of axisymmetric long-dimensional samples during thermal force processing (TFP), which is the simultaneous application of force and temperature effects for comprehensive improvement of geometric characteristics and physical and mechanical parameters of the workpiece material. This technology is used at various stages of technological processes of parts manufacturing, but its main task is to ensure the axis straightness and the specified distribution of residual technological stresses at the procuring stage. The disadvantage of TFP is that the axial deformation proceeds nonuniformly along the workpiece axis. The core process parameter is the deformation, the control of which is a key factor ensuring the TFP efficiency. The authors studied the plastic strain distribution over the sections of long-length workpieces with different deformation degrees. The study involved the assessment of strain uniformity over the workpiece sections, taking into account the stage of the stress-strain relation at the end of the loading cycle. Based on the concepts of plastic deformation as an auto-wave process, the authors selected the range of technological modes corresponding to the most uniform strain distribution along the workpiece axis with complete processing of the entire workpiece volume. This range corresponds to the stage of parabolic hardening of the plastic flow curve with the formation of the maximum number of stationary zones of localized plasticity. Rheological modeling allows identifying the control points that specify the boundaries of the plastic flow curve stages at various loading parameters, including temperature. To improve the reliability of determining the actual deformation under production conditions, the authors proposed modernizing the TFP process monitoring method by fixing the deformation on a limited workpiece section using the optical technique. The statistical analysis of the strain distribution over the sections for the samples confirms the correctness of this approach. The application of the proposed control method will ensure the most uniform distribution of plastic deformation due to the reliable enter of the workpiece deformation to the range of strain values corresponding to the stage of parabolic hardening of the plastic flow curve.

scholarly journals Design of modified 2-degree-of-freedom proportional–integral–derivative controller for unstable processes

2020 ◽  
Vol 53 (7-8) ◽  
pp. 1465-1471
Author(s):  
Ziwei Li ◽  
Zheng Xu ◽  
Ridong Zhang ◽  
Hongbo Zou ◽  
Furong Gao
Keyword(s):  
Control Method ◽  
Direct Synthesis ◽  
Degree Of Freedom ◽  
Proportional Integral Derivative ◽  
Outer Loop ◽  
Set Point ◽  
Proportional Integral ◽  
Point Tracking ◽  
Disturbance Suppression ◽  
Unstable Processes

Concerning first-order unstable processes with time delays that are typical in chemical processes, a modified 2-degree-of-freedom proportional–integral–derivative control method is put forward. The system presents a two-loop structure: inner loop and outer loop. The inner loop is in a classical feedback control structure with a proportional controller intended for implementing stable control of the unstable process; the outer loop is in a 2-degree-of-freedom structure with feedforward control of set points, where the system’s tracking response of set points is separated from its disturbance response. To be specific, the system has a feedforward controller that is designed based on the controlled object models and mainly used for regulating the system’s set point tracking characteristics; besides, it has a feedback controller that is designed on the ground of direct synthesis of disturbance suppression characteristics to improve the system’s disturbance rejection. To verify the effectiveness, the system is put into a theoretical analysis and simulated comparison with other methods. Simulation results show that the system has good set point tracking characteristics and disturbance suppression characteristics.

Enhanced variable universe fuzzy proportional–integral–derivative control of structural vibration with real-time adaptive contracting–expanding factors

2021 ◽  
pp. 107754632110026
Author(s):  
Gang Liu ◽  
Wei Jiang ◽  
Qi Wang ◽  
Tao Wang
Keyword(s):  
Real Time ◽  
Control Method ◽  
Magnetorheological Damper ◽  
Frame Structure ◽  
Structural Vibration ◽  
Proportional Integral Derivative ◽  
Proportional Integral ◽  
Variable Universe ◽  
Proportional Integral Derivative Control ◽  
Derivative Control

A conventional variable universe fuzzy proportional–integral–derivative control approach is widely used for semi-active control in mechanical engineering. The performance of the controller is dependent on an optimal selection of parameters of the contracting–expanding factors. An improved variable universe fuzzy proportional–integral–derivative control algorithm is developed in this study where these parameters are automatically determined in real-time according to the error in the controlled responses and its change rate based on fuzzy logic control. The proposed method is numerically and experimentally illustrated with a three-story frame structure with a magnetorheological damper. The amplitude of displacement, velocity, and acceleration at all floor levels under the proposed control method are smaller than those obtained from existing proportional–integral–derivative, fuzzy, and conventional variable universe fuzzy methods.

scholarly journals Extended state observer–based nonlinear cascade proportional–integral–derivative control of the nano quadrotor

2016 ◽  
Vol 8 (12) ◽  
pp. 168781401668079 ◽  
Author(s):  
Xiaoran Li ◽  
Mou Chen
Keyword(s):  
Control Method ◽  
Design Procedure ◽  
State Observer ◽  
Extended State Observer ◽  
Model Parameters ◽  
Proportional Integral Derivative ◽  
Extended State ◽  
Proportional Integral Derivative Controller ◽  
Proportional Integral ◽  
Tracking Differentiator

The nano quadrotor is a nonlinear multi-input and multi-output system with strong coupling, which causes difficulties in control law design. In order to achieve a favorable performance, an extended state observer–based nonlinear cascade proportional–integral–derivative controller is proposed in this article. First, the nano quadrotor platform is built, and the dynamic model is established. Second, a novel and practical measuring method is given to obtain model parameters. Then, based on the active disturbance rejection control method, the design procedure of the extended state observer–based nonlinear cascade proportional–integral–derivative controller is presented. In the developed controller, a tracking differentiator is involved to extract the signals of gyroscope, and extended state observer is used to estimate the disturbance. To obtain a better performance of tracking differentiator and extended state observer, a systematic parameter-tuning method is studied. Finally, simulation results are given to demonstrate the efficiency of the proposed controller.

The Application of Artificial Intelligence Technology in the Selective Laster Sintering

2014 ◽  
Vol 1037 ◽  
pp. 236-239
Author(s):  
Li Yuan Cai ◽  
Qing Shun Wang ◽  
Wei Sun
Keyword(s):  
Neural Network ◽  
Artificial Intelligence ◽  
Bp Neural Network ◽  
Research Method ◽  
Control Method ◽  
Laser Sintering ◽  
Sintering Process ◽  
Optimal Parameters ◽  
Artificial Intelligence Technology ◽  
Neural Network Algorithm

Based on laser sintering constituency as the research object, this paper aimed at the perspective of artificial intelligence technology. It uses the new control theory and research method of BP neural network algorithm and tries to provide reference for optimizing the sintering process of laser district. This paper argues that the application of artificial intelligence technology to laser sintering constituency. Through the simulation, it can make up for the inadequacy of the traditional control method. Under certain conditions, the goal of process optimization will be achieved by finding the optimal parameters.

scholarly journals A Self-Tuning Proportional-Integral-Derivative-Based Temperature Control Method for Draw-Texturing-Yarn Machine

2017 ◽  
Vol 2017 ◽  
pp. 1-17 ◽  
Author(s):  
Rong Song ◽  
Shuting Chen
Keyword(s):  
Parameter Identification ◽  
Temperature Control ◽  
Control Method ◽  
Fast Time ◽  
Fuzzy Pid ◽  
Proportional Integral Derivative ◽  
Proportional Integral ◽  
Self Tuning ◽  
Set Up ◽  
Control Accuracy

Owing to the fast time-varying characteristics, the temperature control for draw-texturing-yarn (DTY) machine has higher technical difficulties and results in challenges for system energy optimization. To address the matter, a self-tuning proportional-integral-derivative- (ST-PID-) based temperature control method is proposed. Referring to the technical procedures of DTY machine, a thermodynamic model is set up. Then, a ST-PID minimum phase control system is constructed by the pole-point placement method. Subsequently, an artificial neural network based forgetting factor searching (ANN-FFS) algorithm is developed to optimize the system parameter identification. The numerical cases show that the proposed ANN-FFS algorithm can improve the parameter identification process, and the average identifying efficiency (K>15) can increase by more than 50%; compared with the fuzzy PID controller, the proposed ST-PID method can increase the control accuracy nearly 3 times for the static temperature ascending. The experimental results prove that the proposed ST-PID method has better abilities of characteristics tracing and anti-interference and can restrain the temperature fluctuation caused by objective switching and the factual control accuracy reaches 3 times that of fuzzy PID method.

Design and verification of slip rate control system for straight line travel of high clearance self-propelled sprayer

2021 ◽  
pp. 095440702110320
Author(s):  
Wei Li ◽  
Enrong Mao ◽  
Suiying Chen ◽  
Zhen Li ◽  
Bin Xie ◽  
...  
Keyword(s):  
Control System ◽  
Field Test ◽  
Rate Control ◽  
Control Method ◽  
Slip Rate ◽  
Threshold Value ◽  
Proportional Integral Derivative ◽  
Proportional Integral ◽  
Speed Mode ◽  
High Clearance

A slip rate control system aimed at improving the working efficiency and driving stability of a high clearance sprayer was developed. First, the two-pump, two-anti-slip control (ASC) valve, four-motor “X” drive scheme hydraulic slip rate control system was designed, and a mathematical model of the system as well as a vehicle dynamics model were established. The system includes a slip rate control strategy, a proportional-integral-derivative control method and a fuzzy adaptive proportional-integral-derivative sprayer control method. To verify the performance of the system, a simulation model was developed using MATLAB/Simulink, and the performance of the two control methods were compared. Additionally, an actual vehicle test platform was built based on 3WPG-3000 high clearance self-propelled sprayer independently developed by the research group. The simulation results revealed that when a wheel slipped, the slip rate control system was able to control the wheel slip rate and keep it within the threshold value of 0.1, thus meeting the operating requirements of the sprayer. The field test results revealed that in field operations with a low adhesion coefficient, the system was able to maintain a nearly unchanged wheel speed in both fixed speed mode and variable speed mode, maintaining a slip rate below the target of 0.1 “when in a straight running mode” in both cases. Altogether, the results of the simulation and field test verify the stability, accuracy, and practicability of the system.

scholarly journals Digital TV Network Management System Based on WEB

2022 ◽  
Vol 2146 (1) ◽  
pp. 012024
Author(s):  
Wei Qi ◽  
Chun Ying ◽  
Sheng Yong ◽  
Guizhi Zhao ◽  
Lihua Wang
Keyword(s):  
Artificial Intelligence ◽  
Deep Learning ◽  
Control Method ◽  
Digital Tv ◽  
Network Management System ◽  
Snake Robot ◽  
Intelligent Machines ◽  
Artificial Intelligence Technology ◽  
Dynamic Obstacle Avoidance ◽  
Dynamic Obstacle

Abstract With the development and popularization of computer artificial intelligence technology, more and more intelligent machines are gradually produced. These intelligent machines have brought great convenience to people’s lives. This paper studies the control method of snake robot based on environment adaptability, which mainly explains the construction and stability of multi-modal CPG model. In addition, this paper also studies the trajectory tracking and dynamic obstacle avoidance of mobile robot based on deep learning.

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