检索结果-内蒙古大学图书馆

6th International Symposium on Computational Intelligence and Design (ISCID)

作者： Zhang, Yang Liu, Chaoying Song, Xueling Yan, Zhifei Hebei Univ Sci & Technol Inst Elect Engn Shijiazhuang 050018 Peoples R China Hebei Univ Sci & Technol Polytech Coll Shijiazhuang 050018 Peoples R China

ISBN: (纸本)9780769550794

The temperature control of the rectification column is an important part of distillation process control system. For the time-delay and parameter time-varying characteristics in rectification column temperature control system, it puts forward neural network self-tuning pid controller method which combines the advantages of traditional pid control and neural network radial basis function (RBF). From the simulation experiment results it shows that RBF neural network pid controller gets much better control effect, and it verifies the effectiveness of the proposed method.

关键词： Rectification column neural network pid controller RBF neural network Simulation

来源：评论

学校读者我要写书评

暂无评论

A Heading Control Strategy Based On neural network pid controller 32

A Heading Control Strategy Based On Neural Network PID Contr...

引用

32nd Chinese Control And Decision Conference (CCDC)

作者： Zhao, Qin Zhang, Huajun Cheng, Zihui Wuhan Univ Technol Sch Automat Wuhan Peoples R China

ISBN: (纸本)9781728158556

Aiming at the problem that the motion characteristics of ships sailing at sea or inland rivers are time varying and nonlinear, and the heading is difficult to control in real time and accurately, this paper proposes a heading control strategy based on neural network pid controller. The neural network pid controller imitates the structure of neural network. A series of formula derivations can prove that the output of the controller has proportional, integral and differential effects on the error. The parameters of this neural network pid controller are adaptively adjusted in real time online according to the error and the rate of error change. Therefore, the ship control system can still output the optimal control strategy in real time under the complicated and changeable operating environment. Matlab / Simulink is used for simulation. The simulation results prove that the heading control strategy based on neural network pid controller has obvious superiority in real-time and precise control of heading.

关键词： Ship heading control neural network pid controller Online learning

来源：评论

学校读者我要写书评

暂无评论

A Heading Control Strategy Based On neural network pid controller

A Heading Control Strategy Based On Neural Network PID Contr...

引用

第32届中国控制与决策会议

作者： Qin Zhao Huajun Zhang Zihui Cheng School of automation Wuhan University of Technology

Aiming at the problem that the motion characteristics of ships sailing at sea or inland rivers are timevarying and nonlinear,and the heading is difficult to control in real time and accurately,this paper proposes a heading control strategy based on neural network pid *** neural network pid controller imitates the structure of neural network.A series of formula derivations can prove that the output of the controller has proportional,integral and differential effects on the *** parameters of this neural network pid controller are adaptively adjusted in real time online according to the error and the rate of error ***,the ship control system can still output the optimal control strategy in real time under the complicated and changeable operating ***/Simulink is used for *** simulation results prove that the heading control strategy based on neural network pid controller has obvious superiority in real-time and precise control of heading.

关键词： Ship heading control neural network pid controller Online learning

来源：评论

学校读者我要写书评

暂无评论

Optimization of engine speed neural network pid controller based on genetic algorithm

Optimization of engine speed neural network PID controller b...

引用

2011 Fourth International Symposium on Computational Interlligence and Design [第四届计算智能与设计国际会议 ISCID 2011]

作者： Hua-yun CAO Fu-ming PENG School of Automation Nanjing University of Science and Technology Nanjing China School of Automation Nanjing University of Science and Technology Nanjing China

Engine-Dynamometer system is a two-input, dual output system with nonlinear, time-varying characteristics of large inertia,and exists coupling within the system input and output. Using the traditional pid controller, the control is often difficult to achieve the desired effectln addition, at the production site,because of being cumbersome and precision tuning effects, the traditional pid parameter tuning methods can lead to poor control of engine speed. In this paper, an engine speed neural network pid controller based on genetic algorithm which use genetic algorithm to optimizate three control parameters of neural network pid and achieving the system input and output decoupling control is *** results show that the genetic algorithm optimizating engine speed neural network pid control system can effectively improve the accuracy ,enhance stability and fast of the system, and also have increased the engine speed control effect.

关键词： Engine speed genetic algorithm neural network pid controller decoupling control

来源：评论

学校读者我要写书评

暂无评论

An Inverted Differential Mechanism Capable of Achieving Very Large Amplification Ratio: Design and Control

引用

IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING 2025年 22卷 7546-7555页

作者： Wu, Houqi Chen, Guimin Sch Mech Engn State Key Lab Mfg Syst Engn Sch Mech Engn Xian 710049 Peoples R China Xi An Jiao Tong Univ Sch Mech Engn Shaanxi Key Lab Intelligent Robots Xian 710049 Peoples R China

A multitude of flexure-based displacement amplifiers have been developed to amplify piezoelectric actuators for achieving both high-precision motion and large output stroke. Single-stage amplifiers are compact but provide only amplification of several times, while multi-stage amplifiers are able to achieve amplification of dozens of times but are generally bulky in structure. In this work, a displacement amplifier with only a single stage displacement amplifier, which shows the capability of obtaining a very large amplification ratio, is proposed. The displacement amplifier contains two semi-bridge mechanisms with a slight geometric difference between them. This slight difference makes the amplifier require a very small input while achieving a large displacement at the output, leading to a very large amplification ratio. A kinetostatic model considering the nonlinearities in the deflections of both the flexure hinges and the links for the amplifier is developed, based on which the parameters of the amplifier are optimized to maximize the amplification ratio, resulting in an amplifier exhibiting an amplification ratio of 107. The optimization results were validated by those of a finite element model, proving the effectiveness and correctness of the proposed amplifier and the kinetostatic model. The finalized design was prototyped and the measured amplification ratios in a bilateral output mode and a unilateral output mode are 98.10 and 88.42, respectively. A neural network pid controller was designed for the displacement amplifier, with a maximum trajectory tracking error less than 4.7% of the displacement amplifier was achieved.

关键词： Fasteners Bridges Differential amplifiers Vectors Mathematical models Piezoelectric actuators neural networks Lead zirconate titanate Automation Accuracy Flexure-based mechanism displacement amplifier kinetostatic model neural network pid controller

来源：评论

学校读者我要写书评

暂无评论

neural network pid control for combustion instability

引用

COMBUSTION THEORY AND MODELLING 2022年第2期26卷 383-398页

作者： Zhang, Long Li, Shan Xue, Yuan Zhou, Hua Ren, Zhuyin Tsinghua Univ Sch Aerosp Engn Beijing Peoples R China Tsinghua Univ Dept Energy & Power Engn Beijing Peoples R China Tsinghua Univ Inst Aero Engine Beijing Peoples R China

Considerable research studies have been reported on developing effective active control means to mitigate combustion instability. In this work, a neural network pid (NN-pid) controller is proposed and demonstrated to suppress the oscillating pressure in a cylindrical Rijke tube, for which the combustion instability is modelled by a 1D acoustic network model together with linear and nonlinear flame models. The flame model is based on the classical n - tau model ?ltered by a first-order low pass ?lter. The nonlinearity of the flame model is realised using a gain function saturated with velocity perturbation. A fuel valve and a loudspeaker are adopted as two independent control actuators. Results show that system oscillation begins to attenuate when the NN-pid control starts. The attenuation rate using a fuel valve as the actuator is faster than that using a loudspeaker. For nonlinear combustion oscillations, the NN-pid controller could inhibit the reference pressure oscillation in the linear growth and saturation processes. A maximum overshoot of 2.3% could occur when the loudspeaker is used as the actuator to suppress system oscillation. The NN-pid controller is not affected by noise with a fuel valve or the loudspeaker and can effectively suppress and eliminate the system pressure oscillation in different oscillating stages with different flame models.

关键词： combustion instability acoustic network linear and nonlinear flame models neural network pid controller noise effects

来源：评论

学校读者我要写书评

暂无评论

A Hybrid CKF-NNpid controller for MIMO Nonlinear Control System 13

A Hybrid CKF-NNPID Controller for MIMO Nonlinear Control Sys...

引用

13th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON)

作者： Sento, Adna Kitjaidure, Yuttana King Mongkuts Inst Technol Ladkrabang Sch Elect Engn Fac Engn Bangkok 10520 Thailand

ISBN: (纸本)9781467397490

This paper presents a detailed study to demonstrate the online tuning dynamic neural network pid controller to improve a joint angle position output performance of 4-joint robotic arm. The proposed controller uses a new updating weight rule model of the neural network architecture using multi-loop calculation of the fusion of the gradient algorithm with the cubature Kalman filter (CKF) which can optimize the internal predicted state of the updated weights to improve the proposed controller performances, called a Hybrid CKF-NNIPD controller. To evaluate the proposed controller performances, the demonstration by the Matlab simulation program is used to implement the proposed controller that connects to the 4-joint robotic arm system. In the experimental result, it shows that the proposed controller is a superior control method comparing with the other prior controllers even though the system is under the loading criteria, the proposed controller still potentially tracks the error and gives the best performances.

关键词： Robotic arm control system neural network pid controller cubature Kalman filters adaptive learning algorithm

来源：评论

学校读者我要写书评

暂无评论

An Intelligent System Architecture for Meal Assistant Robotic Arm 9

An Intelligent System Architecture for Meal Assistant Roboti...

引用

9th International Conference on Knowledge and Smart Technology (KST)

作者： Sento, Adna Srisuk, Pannawit Kitjaidure, Yuttana King Mongkuts Inst Technol Ladkrabang Fac Engn Dept Elect Engn Bangkok 10520 Thailand

ISBN: (纸本)9781467390774

A meal assistant robotic arm is necessary for disable people who cannot move by themselves such as paralysis patients, severely handicapped people, etc. Several research articles have been proposed. However, the system designs for the meal assistant robotic arm have been found for a small number of the improvements. Therefore, this paper presents a detailed study to innovate the meal assistant robotic arm. The proposed system design consists of four parts;1) feature extraction algorithm using the Microsoft Kinect sensor to create the target position in 3-dimensional Cartesian coordinate, 2) inverse kinematic algorithm to convert the Cartesian coordinate into the joint angles, 3) controller algorithm. The proposed controller uses a new weight updating rule model of the neural network using multi-loop calculation based on the fusion of the gradient algorithm with the cubature Kalman filter (CKF) which can optimize the internal predicted state of the updated weights to improve the proposed controller performances, and 4) the 4-joint robotic arm. To evaluate the performances, the Matlab program is used to implement the overall system. The experimental results show that the meal assistant robotic arm system is able to track the human mouth in the 3-dimensional coordinate system.

关键词： Meal assistant robotic arm neural network pid controller Cubature Kalman filters Inverse kinematic algorithm

来源：评论

学校读者我要写书评

暂无评论

pid-neural controller based on AVR Atmega128

PID-Neural Controller based on AVR Atmega128

引用

10th International Conference on Control, Automation, Robotics and Vision

作者： Xuan Khanh Pham Doan Que Anh Vo Ngoc Hal Nguyen The Phong Cao Hanoi Univ Ind Fac Elect Engn Hanoi Vietnam Hanoi Univ Technol Dept Automat Control Hanoi Vietnam

ISBN: (纸本)9781424422869

This paper concerns designing of pid-neural controller, a neural network pid controller based on AVR ATmega128. It also discusses the corresponding learning algorithm, Brandt-Lin algorithm and the application of the pid-neural controller to a DC motor. This new controller has more advantage than the traditional one, such as more convenient in parameter regulation, better robust, more independence and adaptability on the plant, etc.

关键词： pid-neural controller neural network pid controller Atmega128 learning algorithm Brandt-Lin algortihtm parameter regulation

来源：评论

学校读者我要写书评

暂无评论

A Hybrid CKF-NNpid controller for MIMO Nonlinear Control System

A Hybrid CKF-NNPID Controller for MIMO Nonlinear Control Sys...

引用

International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology

作者： Adna Sento Yuttana Kitjaidure School of Electronics Engineering Faculty of Engineering King Mongkut's Institute of Technology Ladkrabang Bangkok 10520 Thailand

ISBN: (纸本)9781467397506

关键词： Robotic arm control system neural network pid controller Cubature Kalman filters Adaptive learning algorithm

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：