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山东大学毕业设计 内含所有内容。源代码 电路图等等。系统由监控主机（PC机）和多个水质监测子机组成，它们之间借助无线通信平台实现远程水质信息收集和监测控制，从而可全面、准确、及时地掌握水域的水质信息，水质监控中心会实时做出水质报告和水质污染预报，为水资源保护、监督、管理和决策提供了有力的支持手段。-System consists of monitoring the host (PC) and various water quality monitoring sub-machine compone
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本书涉及的研究方法主要应用于油田生产的实际工作中，包括一般储层参数预测、薄互油藏参数预测、火山岩储层参数预测和储层随机模拟等问题，同时还涉及了石油工业中的油管缺损检测、海底输油管道腐蚀检测等应用问题，对污水处理絮凝过程的智能优化控制及移动机器人的全局和局部路径规划等问题的应用也进行了一定的研究。-Book of research methods involved are mainly used in oil field production of practical work, includi
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:针对时滞系统的特点和采用神经网络单值预测控制存在的不足,提出了多步超前预测与补偿的控制算
法,有效地增加了控制力度,改善了动态性能,并论述了增加的预测与补偿步数与稳定的关系
-With regards to the characteristics of time-delay system and the weakness of single predictive control, this pa-
per puts forward a control scheme of multi
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动态矩阵的预测控制源程序，可以实现预测控制中的模型预测和优化算法。- this pa-
per puts forward a control scheme of multi-step-ahead prediction and compensation, which increases control power effectively,
and improves dynamic characteristics ofthe system. The paper also discusses
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动态矩阵的预测控制源程序，可以实现预测控制中的模型预测和优化算法。- this pa-
per puts forward a control scheme of multi-step-ahead prediction and compensation, which increases control power effectively,
and improves dynamic characteristics ofthe system. The paper also discusses
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预测控制的程序,主要是关于预测控制的应用的小例子- this pa-
per puts forward a control scheme of multi-step-ahead prediction and compensation, which increases control power effectively,
and improves dynamic characteristics ofthe system. The paper also discusses the relat
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基于信道的历史信息来预测不同信道的未来可用时间可以帮助CR选择一个最佳信道进行信息传递。不同的预测准则应用到周期或是随机的开关模式中。一个CR可以学习以往不同信道的模式。我们提出一个简单的分类和学习方法去检测模式的类型和收集需要的信息用于智能信道的选择。MATLAB仿真结果显示提出的方案在随机信道的随机和周期模式中都有优越的表现。随着时间的变化，新到的切换次数减少到55 ，并且延迟时间也相应减少，而吞吐量却在提高。-Prediction of future availability times
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CDMA系统中的反向预测功率控制算法,一个使用LabVIEW实现的CDMA算法。-CDMA system reverse prediction power control algorithm, an algorithm using the LabVIEW implementation of CDMA.
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a robust 1 prediction-based pole placement
control design is introduced for CDMA uplink power control via the LMI method from the state-space perspective
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光电稳像系统跟踪控制与脱靶量预测方法研究，硕士论文，很好很详细-Optical image stabilization system to track the amount of control and off-target prediction method, master' s thesis, very very detailed
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This paper deals with digital control of a series
active filter integrated with a diode rectifier where the series
active fdter is controlled to function as a current source.
A predictive current regulator is considered for the series ac-
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Model Predictive Control code using Matlab software:
How Plants Are Used In Model Predictive Control.
Blocking and typical Sampling Instant.
Prediction and Control Horizons.
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利用新陈代谢灰色预测、样本自适应BP 神经网络和时间序列分析分别进行风电功率实时预测和日前预测，并采用熵值取权法确定组合权重，引入自控机制，构建反馈，提出组合预测法和基于时间序列的卡尔曼滤波法。研究结果表明，组合预测模型能减少各预测点较大误差的出现，而卡尔曼滤波能大幅消减原始序列的波动影响。-Use of metabolic gray forecast, sample adaptive BP neural network and time sequence analysis respective
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时变大滞后系统的自适应灰色预测PID控制,不错的参考文献。-Time-varying systems with adaptive grey prediction PID control of large time delay, a good reference.
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The 4g wireless uses Orthogonal Frequency Division Multiplexing (OFDM), Ultra Wide Radio Band (UWB), and Millimeter wireless. Data rate of 20mbps is employed. Mobile speed will be up to 200km/hr. The high performance is achieved by the use of long te
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The doubly fed induction generator (DFIG) is widely
used in wind energy. This paper proposes a model-based predictive
controller for a power control of DFIG. The control law is derived
by optimization of an objective function that considers the
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Predictive direct power control (P-DPC) applied
to voltage source pulse-width-modulation (PWM) rectifier was
introduced in this paper. Based on the model of power
prediction, voltage vectors were selected according to
minimizing power errors
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Generalized prediction control theory and application on exoskeleton systems
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有关模型预测MPC的电子书，包括集中式和分布式，包含基础知识的介绍-MPC about the model prediction of e-books, including centralized and distributed, covers a basic knowledge
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《无人驾驶模型预测控制》由北京理工大学陈慧岩教授团队编著，详细介绍了应用模型预测控制理论进行无人驾驶车辆控制的基础方法，结合运动规划与跟踪实例详细说明了预测模型建立、方法优化、约束处理和反馈校正的方法，给出了Matlab仿真代码和详细图解仿真步骤。
对照原书可更方便/快速的学习代码(The prediction control of driverless model is compiled by Professor Chen Huiyan of Beijing University of tec
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