共查询到19条相似文献，搜索用时 551 毫秒
1.
通过对广义预测控制性能指标函数中控制加权序列Qj（z-1）的配置给定,导出了具有PID算法结构的广义预测控制律,借助广义预测控制算法参数的递推关系链,自动优化整定PID调节参数,并在冶金实验炉温控制中实现了广义预测PID控制。 相似文献
2.
为了解决目前常用的非线性预测模型算法中过学习、存在局部极小值等不易解决的问题,本文提出一种基于最小二乘支持向量机对非线性过程建模并用广义预测控制进行在线滚动控制的算法。仿真结果表明,该控制算法具有很好的控制性能。 相似文献
3.
分析了多因性多址协议及并应用于Web传输,在QoS异步预测算法提出和研究基础上,提出一种多因性多址协议QoS异步预测算法,对Web通信信道优化建模,建模包括拥塞控制,差错控制设计,实现对网络传输中帧率和比特率的自适应控制。仿真实验表明,新算法能克服传统算法丢包率随着输出总码率的升高而升高,导致丢包率不符合QoS标准的问题,算法能有效应对大规模Web资源传输的需求,比传统方法具有优越性和普适性,收敛性好,自适应调整速度快,在大存储量网络资源传输通信中具有可观的应用前景。 相似文献
4.
本文针对当前的排序推荐算法研究中,大部分算法没有充分利用数据集中的有效信息的问题,提出一种自适应的成对排序推荐算法,该算法同时使用了显式评分和隐式反馈信息,提高了算法的准确率的观点。在个性化推荐行业起到一定的积极作用。如付诸现实将产生约20万元的经济效益。 相似文献
5.
自动控制技术在当今的工程和科学发展中起着极为重要的作用。自动控制理论在发展过程中,形成了经典控制理论和现代控制理论。然而,在实际的工业控制过程中,常常存在着各种不确定性。为了满足日益复杂的工业过程自适应控制的需要,出现了预测控制,并在工业控制领域中得到了成功的应用。文章设计了一种Fuzzy-PID广义预测复合控制器,使模糊控制、PID控制与广义预测控制3种控制算法结合起来。通过该控制器可以有效的根据不同的工业生产环境来选择其适合的控制方法,以提高其生产效率,使控制得到充分的优化。 相似文献
6.
贾维宏 《科技成果管理与研究》2012,(3):54-57
提出一种针对一类可分非线性系统的广义预测控制算法。首先利用对角回归型神经网络（Diagonal Recurrent Neura Network,简称DRNN）逼近非线性子系统,线性子系统的模型采用受控自回归积分滑动平均模型（CARIMA）,从而建立了一种适合于非线性系统的广义预测模型。在该算法中引入柔化系数矩阵,避免矩阵求逆的计算,减少了在线计算量。仿真结果表明,该广义预测控制算法具有响应速度快、控制效果好的特点。 相似文献
7.
8.
《科技成果管理与研究》2013,(11):F0004-F0004
使用望远镜特别是大型望远镜时,大气湍流引起的动态波前误差使成像模糊并不断漂移,这一问题一直困扰着天文界和光学界。姜文汉院士自1979年起,开始研究自适应光学,通过对动态波前误差的实时探测一控制一校正,使光学系统具有自动校正外界扰动,保持理想性能的能力。自适应光学成为高分辨力光学观测和高集中度光能传输中的重要核心技术。附图是对一颗双星用自适应光学校正大气动态干扰前后的成像结果。 相似文献
9.
10.
近年来,随着我国城市化的加速发展,大量的高层建筑物随之产生,其安全问题也日益受到人们的关注,高层建筑物的变形问题就是其中之一,而常用的预测方法对高层建筑物变形监测存在一些不足。基因表达式编程是一种基于生物基因结构而发明的一种新型自适应演化算法,已经在金融、气象和灾害预警等领域广泛应用。因此,本文将探讨基因表达式编程在高层建筑物变形预测中的应用。 相似文献
11.
本文将模糊控制器的在线参数自整定算法与积分抑制策略相结合提出一种利用积分抑制的参数自整定模糊控制器。通过对几个二阶对象的仿真实验表明，它不但能改善模糊控制系统的动态性能，而且能有效地消除系统余差，具有使用价值，可用于电机传动系统模糊控制的研究。 相似文献
12.
《Journal of The Franklin Institute》2018,355(18):9036-9052
A new aircraft guidance law utilizing predictive control algorithm is proposed. Compared with extended proportional navigation guidance law, this guidance law is designed specifically for using against a maneuverable target. It can track the target maneuver effectively. Uncertainty in the predicted target's future maneuvering is handled by constructing a stochastic predictive cost function and utilizing the stochastic minimum principle to deduce a predictive control algorithm. The guidance law is established by adopting the continuous approximation method into the continuous predictive control algorithm. The simulation results demonstrate that the stochastic predictive guidance law has the ability of trajectory prediction. Compared with the PID proportional navigation guidance law, the stochastic predictive guidance law has smaller overload and can intercept the maneuvering target more effectively. 相似文献
13.
《Journal of The Franklin Institute》2023,360(8):5658-5688
An adaptive sliding mode-model predictive control for the path following of intelligent unmanned vehicle is given in this paper. On account of excellent performances of the sliding mode structure, this algorithm can not only effectively estimate the uncertainty of the vehicle system to further improve the following accuracy, but minish the amount of calculation in comparision with model predictive control. Then, the following accuracy between the real system and the theoretical model can be compensated by the fractional order coefficient of controller. Therefore, an adaptive fractional order sliding mode-fractional order model predictive control is designed to follow the path of the intelligent unmanned vehicle. Meanwhile, the robust stability and control accuracy of the associated control algorithm are proved. Finally, different paths are designed to verify the theoretical analysis of the control performance in the controllers. 相似文献
14.
吴巍 《科技成果管理与研究》2009,(9):63-66
提出了预测函数控制（PFC）与PID控制结合的新方法．并针对典型工业过程控制．分析了预测函数控制的基本原理和特点。基于Smith预估器．给出了工业过程控制中改进的预测函数控制算法,并用MATLAB进行仿真实验．仿真结果也表明其对被控系统有良好的鲁棒性、抑制干扰能力和跟踪性能。 相似文献
15.
《Journal of The Franklin Institute》2023,360(5):3657-3676
This paper presents a data-driven predictive control method for optimizing the energy consumption of air-cooled data centers with unknown system model parameters. First, based on the measurable data of the studied system, the subspace predictive control (SPC) method is adopted to improve the energy use efficiency of the data center by regulating the power allocation of the server racks and the supply temperature of cold air, while ensuring the safe operating environment of the electronic equipment. Furthermore, a reasonable event-triggered law is designed to solve the problem of the low computational efficiency of the conventional SPC method. The simulation results illustrate that the designed event-triggered law can improve the computational efficiency of the algorithm while maintaining the control performance of the algorithm, which verifies its application prospect in practice. 相似文献
16.
《Journal of The Franklin Institute》2022,359(7):3024-3045
This paper presents two stochastic model predictive control methods for linear time-invariant systems subject to unbounded additive uncertainties. The new methods are developed by formulating the chance constraints into deterministic form, which are treated in analogy with robust constraints, by using the probabilistic reachable set. The first one is the time-varying tube-based stochastic model predictive control algorithm, which is designed by employing the time-varying probabilistic reachable sets as tubes. The second one is the constant tube-based stochastic model predictive control algorithm, which is developed by enforcing a constant tightened constraint in the entire prediction horizon. In addition, the soft constraints are proposed to associate with the state initialization in the algorithms to enhance the feasibility. The algorithm feasibility and closed-loop stability results are provided. The efficacy of the approaches is demonstrated by means of numerical simulations. 相似文献
17.
Min-Rong Chen Guo-Qiang Zeng Xiao-Qing Xie 《Journal of The Franklin Institute》2018,355(17):8266-8295
How to design a set of optimal distributed load frequency controllers for a multi-area interconnected power system is an important but still challenging issue in the field of modern electric power systems. This paper presents an adaptive population extremal optimization-based extended distributed model predictive load frequency control method called PEO-EDMPC for a multi-area interconnected power system. The key idea behind the proposed method is formulating the dynamic load frequency control issue of each area power system as an extended distributed discrete-time state-space model based on an extended state vector, obtaining a distributed dynamic extended predictive model, and rolling optimization of real-time control output signal by adopting an adaptive population extremal optimization algorithm, where the fitness is evaluated by the weighted sum of square predicted errors and square future control values. The superiority of the proposed PEO-EDMPC method to a traditional distributed model predictive control method, a population extremal optimization-based distributed proportional-integral control algorithm and a traditional distributed integral control method is demonstrated by the simulation studies on two-area and three-area interconnected power systems in cases of normal, perturbed system parameters and dynamical load disturbances. 相似文献
18.
率失真优化技术在视频优化编码中起着重要的作用，广泛地应用于宏块模式决策，优化量化等编码模块中。本文将率失真优化编码与码率控制结合起来进行研究，通过对率失真关系的分析，提出了基于率失真优化的复杂度可分级码率控制算法，并根据缓冲区操作模型的位分配约束条件调整码率控制的位分配过程，从而使得该算法能够在达到码率控制的同时也能取得较高的编码效率，并能保证缓冲区不会发生溢出，然后结合场景变换、图像内容分类等主观质量问题研究，提出一种恒定质量码率控制编码算法。 相似文献
19.
《Journal of The Franklin Institute》2021,358(18):9975-10003
Distributed coordination of multi-agent systems (MASs) has been investigated for many years, and fractional-order calculus has been proved that it can model the dynamics more accurately in certain circumstances. Hence, in this paper, combining the above two aspects, the distributed coordination of fractional-order MASs (FOMASs) is researched, which is a promising topic. Besides, in this paper, the uncertainty, inherent nonlinearity and external disturbances are taken into consideration, aiming at achieving the robust consensus tracking. In particular, the uncertain parameters will be identified from an optimization perspective using artificial bee colony algorithm (ABC). Firstly, to ameliorate the performance of the standard ABC, a hybrid ABC (hABC) incorporating two groups of searching mechanisms is designed, it facilitates the identification of unknown parameters. After obtaining the identified parameters, an efficient distributed nonlinear controller is raised to fulfill the robust consensus tracking. Finally, experiments prove that the designed parameters identification approach can successfully estimate the uncertain parameters with high accuracy, besides the designed control algorithm can robustly control the FOMASs. 相似文献