Description: 为了便于进行形象化的理解，本章进行了控制结果的可视化编程。利用Matlab与Borland C++ Builder的程序开发接口，通过建立独立的可执行程序，演示了控制过程中对熨平板进行调节的过程。最终认为，PID控制和人工神经网络控制对控制速度和精度都有了很多的改善；对摊铺机自动调平装置而言，其控制器的设计占有重要的地位。 -To facilitate figurative understanding of this chapter for the control of the results of visual programming. Using Matlab and Borland C Builder program interface, through the establishment of an independent executable, demonstrated the control process for calming the board to adjust the process. Finally, PID control and artificial neural network control to control speed and accuracy have a lot of improvement; right paver automatic leveling device, its controller design occupies an important position. Platform: |
Size: 192085 |
Author:史海红 |
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Description: 人工智能中模糊逻辑算法
FuzzyLib 2.0 is a comprehensive C++ Fuzzy Logic library for constructing fuzzy logic systems with multi-controller support.
It supports all commonly used shape functions and hedges, with full support for the various types of Aggregation, Correlation, Alphacut, Composition, Defuzzification methods.
The latest version of the C++ Fuzzy Logic Class Library contains all the C++ source code and comes complete with a usage example for building a multi-controllers fuzzy logic model.-artificial intelligence, fuzzy logic algorithm FuzzyLib 2.0 is a comprehensi 've Fuzzy Logic C library for constructing fuzzy logic systems with multi-controller support. It supports all commonly used functions a shape nd hedges. with full support for the various types of Aggre the accounts, Correlation, Alphacut, Composition, Defuzzification methods. The latest version o f the C Fuzzy Logic Class Library contains all th e C source code and comes complete with a usage ex ample for building a multi-fuzzy controllers l ogic model. Platform: |
Size: 314181 |
Author:周荷 |
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Description: 为了便于进行形象化的理解，本章进行了控制结果的可视化编程。利用Matlab与Borland C++ Builder的程序开发接口，通过建立独立的可执行程序，演示了控制过程中对熨平板进行调节的过程。最终认为，PID控制和人工神经网络控制对控制速度和精度都有了很多的改善；对摊铺机自动调平装置而言，其控制器的设计占有重要的地位。 -To facilitate figurative understanding of this chapter for the control of the results of visual programming. Using Matlab and Borland C Builder program interface, through the establishment of an independent executable, demonstrated the control process for calming the board to adjust the process. Finally, PID control and artificial neural network control to control speed and accuracy have a lot of improvement; right paver automatic leveling device, its controller design occupies an important position. Platform: |
Size: 193536 |
Author:史海红 |
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Description: 人工智能中模糊逻辑算法
FuzzyLib 2.0 is a comprehensive C++ Fuzzy Logic library for constructing fuzzy logic systems with multi-controller support.
It supports all commonly used shape functions and hedges, with full support for the various types of Aggregation, Correlation, Alphacut, Composition, Defuzzification methods.
The latest version of the C++ Fuzzy Logic Class Library contains all the C++ source code and comes complete with a usage example for building a multi-controllers fuzzy logic model.-artificial intelligence, fuzzy logic algorithm FuzzyLib 2.0 is a comprehensi 've Fuzzy Logic C library for constructing fuzzy logic systems with multi-controller support. It supports all commonly used functions a shape nd hedges. with full support for the various types of Aggre the accounts, Correlation, Alphacut, Composition, Defuzzification methods. The latest version o f the C Fuzzy Logic Class Library contains all th e C source code and comes complete with a usage ex ample for building a multi-fuzzy controllers l ogic model. Platform: |
Size: 314368 |
Author:周荷 |
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Description: 模拟人的思维特点,提出一种新型智能控制器:仿人逻辑预测控制器. 该控制器融合了基于泛布尔代数的逻辑控制器和基于模型的预测控制器的特点, 是一种多值逻辑混合动态系统. Matlab仿真表明, 该控制器在模型匹配时性能良好, 在模型失配时依然能满意运行, 表现出鲁棒性强, 超调量小的特点. 与其它类型人工智能控制器相比, 该控制器结构简单, 物理背景明确, 数学概念清晰, 便于在工业控制领域推广应用.-Simulation of the characteristics of people' s thinking, a new intelligent controller: humanoid logic controller prediction. The controller is based on the integration of pan-Boolean algebra of logic controllers and model-based predictive controller features, is a multi-valued logic hybrid dynamic systems. Matlab simulation show that the controller performance in the model match well when the model mismatch can be satisfied with the operation still showed robust, ultra-tune the characteristics of a small amount. with other types of artificial intelligence controller ratio, the controller structure is simple and clear physical background, the concept of math clear, easy in the field of industrial control application. Platform: |
Size: 267264 |
Author:文豪 |
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Description: 基于NS2的计算机网络虚拟实验室的设计与实现--------硕士学位论文-Intelligent Controller Based on Ant System Algorithm and Fuzzy Inference and Its Application to Bionic Artificial Legs
Platform: |
Size: 2638848 |
Author:hkj |
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Description: 采用神经网络控制的方法。利用人工神经网络的自学习这一特性，并结合传统的PID控制理论，构造神经网络PID控制器，实现控制器参数的自动调整-Control method using neural network. Artificial neural network to learn the characteristics of the self, combined with the traditional PID control theory, structural neural network PID controller, automatically adjust the controller parameters
Platform: |
Size: 1024 |
Author:孙丽媛 |
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Description: Abstract-This paper introduces the new concept of Artificial
Neural Networks (ANNs) in estimating speed and
controlling the separately excited DC motor. The neural
control scheme consists of two parts. One is the neural
estimator, which is used to estimate the motor speed. The
other is the neural controller, which is used to generate a
control signal for a converter. These two networks are
trained by Levenberg-Marquardt back propagation
algorithm. Standard three layer feed forward neural
network with sigmoid activation functions in the input and
hidden layers and purelin in the output layer is used.
Simulation results are presented to demonstrate the
effectiveness and advantage of the control system of DC
motor with ANNs in comparison with the conventional
control scheme. Platform: |
Size: 490496 |
Author:amidi |
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Description: 人工神经网络(Artificial Neural Network)是从生理角度对智能的模拟，具有极
高的学习能力和自适应能力，能够以任意精度逼近任意函数，完成对系统的仿真；
而遗传算法是对自然界生物进化过程的模拟，具有极强的全局寻优能力，这两种
算法都是当下研究较多的智能方法。将这两种方法与常规的 PID 控制相结合，
构成智能 PID 控制器，使其具有参数自整定、自适应的能力，以适应复杂环境
下的控制要求，这一思路对提高控制效果具有很好的现实意义。
-Artificial Neural Network (ANN) is an imitation of the intelligence by the point of physiological. It has a high capacity of learning and adaptive, can approximate any function to arbitrary accuracy, and complete the simulation of the system. The Genetic
algorithm is a simulation of natural biological evolution, which has a strong ability of
global optimization. These two algorithms are more intelligent method of current
research. The idea of combining these two methods with the conventional PID
controller to be a intelligent controller with the abilities of parameter auto-tuning and
adaptive for the requirements of the complex environment, has a high practical
significance of improving the control effect.
Platform: |
Size: 661504 |
Author:baijiaxuan |
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Description: 水资源智能控制器是以先进的微电脑控制技术为核心，以智能卡技术为信息传递媒介而构成的高技术智能化控制设备。具有技术领先、功能完备、安装便捷、使用方便的优点。它解决了水资源管理领域现有的人工查表收费手续的繁杂、水表的损坏、水费的回收不及时等问题，彻底改变了原有的管理模式，实现了预付费购水，提高了水资源的管理水平，实现了现代化管理。-Water resources Intelligent Controller is an advanced microcomputer control technology as the core control equipment consisting of high-tech intelligent smart card technology for information delivery media. With leading technology, full-featured, easy to install, easy to use advantages. It solves the complex management of water resources that currently exist in the field of artificial look-up table charging procedures, the meter is damaged, the recovery of water charges is not timely issue, completely changed the management model, pre-paid purchase of water, improve water the level of resource management, modern management. Platform: |
Size: 100352 |
Author:丁志录 |
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Description: In This paper, the authors propose a Sensorless Direct Torque and Flux Control (DTFC) of
Induction Motor (IM) using two approach intelligent techniques: Mamdani Fuzzy Logic (FL)
controller is used for controlling the rotor speed and Artificial Neural Network (ANN) applied in
switching select stator voltage. We estimated the rotor speed by using the Model Reference
Adaptive Systems (MRAS). The control method proposed in this paper can reduce the torque,
stator flux and current ripples and especially improve system good dynamic performance and
robustness in high and low speeds-In This paper, the authors propose a Sensorless Direct Torque and Flux Control (DTFC) of
Induction Motor (IM) using two approach intelligent techniques: Mamdani Fuzzy Logic (FL)
controller is used for controlling the rotor speed and Artificial Neural Network (ANN) applied in
switching select stator voltage. We estimated the rotor speed by using the Model Reference
Adaptive Systems (MRAS). The control method proposed in this paper can reduce the torque,
stator flux and current ripples and especially improve system good dynamic performance and
robustness in high and low speeds.. Platform: |
Size: 3107840 |
Author:aa |
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Description: 逻辑预测控制 仿人逻辑预测控制器设计. 该控制器融合了基于泛布尔代数的逻辑控制器和基于模型的预测控制器的特点, 是一种多值逻辑混合动态系统. Matlab仿真表明, 该控制器在模型匹配时性能良好, 在模型失配时依然能满意运行, 表现出鲁棒性强, 超调量小的特点. 与其它类型人工智能控制器相比, 该控制器结构简单, 物理背景明确, 数学概念清晰, 便于在工业控制领域推广应用-Simulating characteristics of human intelligent, a new intelligent controller was produced: Human-simulation Logical Predictive Controller(HLPC). This controller can utilize the advantage both in logical controller based on pan-boolean algebra and model-based predictive controller. It is a multi-logic hybrid dynamic system. Simulated results based on Matlab prove that HLPC shows good performance when predictive model matches and satisfactory results when model mismatches, represents better robustness and small overshoot . Compared with other artificial intelligent controller, HLPC has simple structure, clearly physics background and mathematical concepts, thus would make it easy for industrial application. Platform: |
Size: 58368 |
Author:wuming |
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Description: 模拟人类实际神经网络的数学方法问世以来，人们已慢慢习惯了把这种人工神经网络直接称为神经网络。神经网络在系统辨识、模式识别、智能控制等领域有着广泛而吸引人的前景，特别在智能控制中，人们对神经网络的自学习功能尤其感兴趣，并且把神经网络这一重要特点看作是解决自动控制中控制器适应能力这个难题的关键钥匙之一。
-Since the actual neural network simulation of human mathematical methods available, it has gradually become accustomed to this kind of artificial neural network called neural networks directly. Neural network system identification, pattern recognition, intelligent control and other fields have a wide and attractive prospects, especially in intelligent control, people' s self-learning function of neural networks are particularly interested in, and the neural network is seen as an important feature of this One of the keys to solve the automatic control of the key controller' s ability to adapt to this problem. Platform: |
Size: 6144 |
Author:Ryan |
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Description: This paper proposes a new MPPT controller. The proposed
MPPT controller is based on genetic algorithm (GA) optimized
artificial neural network (ANN). For the simulation purpose an
improved model of SPV is used. The MPPT is simulated and
studied using MATLAB software. Platform: |
Size: 304128 |
Author:samir |
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Description: The paper deals with a controller design for the nonlinear processes using genetic
algorithm and neural model. The aim was to improve the control performance using
genetic algorithm for optimal PID controller tuning. The plant model has been
identified via an artificial neural network from measured data. The genetic algorithm
represents an optimisation procedure, where the cost function to be minimized
comprises the closed-loop simulation of the control process and a selected
performance index evaluation. Using this approach the parameters of the PID
controller were optimised in order to become the required behaviour of the control
process. Testing of quality control process was realized in simulation environment of
Matlab Simulink on selected types of nonlinear dynamic processes.-The paper deals with a controller design for the nonlinear processes using genetic
algorithm and neural model. The aim was to improve the control performance using
genetic algorithm for optimal PID controller tuning. The plant model has been
identified via an artificial neural network from measured data. The genetic algorithm
represents an optimisation procedure, where the cost function to be minimized
comprises the closed-loop simulation of the control process and a selected
performance index evaluation. Using this approach the parameters of the PID
controller were optimised in order to become the required behaviour of the control
process. Testing of quality control process was realized in simulation environment of
Matlab Simulink on selected types of nonlinear dynamic processes.
Platform: |
Size: 135168 |
Author:samir |
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Description: Induction motor drive based on direct torque control (DTC) allows high dynamic performance to be obtained with very simple hysteresis control scheme.
Once the DTC is fully and deeply described, its main drawbacks are introduced. One of the goals of the present paper is to overcome one of the worst disadvantage of DTC, which is the existence of a considerable ripple in its torque response. The previously explained DTC limitations involve plenty of nonlinear functions. Therefore, artificial intelligence is suggested to overcome the DTC limitations. Hence, a Fuzzy logic DTC controller, which is based on the classical DTC but includes a fuzzy logic controller, is fully described. We carry out a detailed comparison study between conventional direct torque control
(CDTC) and direct torque fuzzy control (DTFC).
Platform: |
Size: 1419264 |
Author:Youcef |
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Description: This paper presents neural networks based approach
for estimation of the control and operating parameters of Statcom
used for improving voltage profile in a power system, which is
emerging as a major problem in the day-to-day operation of
stressed power systems. Statcom is an important voltage source
converter FACTS device, which can be used in voltage control
mode or reactive power injection mode. For stable operation and
control of power systems it is essential to provide real time
solution to the operator in energy control centers. Artificial neural
networks are proposed here for this task, as they have Platform: |
Size: 285696 |
Author:phdscolar11
|
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