共查询到20条相似文献,搜索用时 250 毫秒
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将PID反馈原理引入广义预测控制(GPC)思想,把GPC目标性能函数改造成具有PI的结构形式,根据反馈时延导出多步控制序列,通过时延补偿器对前向时延进行补偿,使控制性能在网络环境下得到极大改善。控制器结合了PID控制和预测控制的优点,具有较强的鲁棒性和工程意义。构造Lyapunov函数对闭环系统的稳定性进行分析,并通过仿真验证了该算法的有效性。 相似文献
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支持向量机在网络广义预测控制中的应用 总被引:2,自引:2,他引:0
在网络控制系统的研究中,支持向量机(SVM) 在网络广义预测控制中的应用具有良好控制效果和稳定性.为提高网络性能,对网络控制系统进行模型预测,并将SVM作为广义预测控制(GPC) 算法中的预测模型,采用支持向量机的广义预测控制算法.进行预估技术和队列机制,对被控对象选择最合适的控制信号,降低了时延对网络控制系统的危害性,并通过Matlab上仿真结果表明,与PID控制相比较,基于SVM的GPC算法在网络控制方面超调量较小,调整时间较短,控制效果更好. 相似文献
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自适应Smith补偿器在基于IP的网络控制系统中的应用 总被引:1,自引:0,他引:1
在基于IP网络的网络控制系统(NCS s)中,网络诱导时延变化显著且往往大于一个采样周期.本文引用数据通信中应用广泛的网络回程时间来估计NCS s中时变的全回路网络诱导时延,并提出了一种新的自适应Sm ith补偿器.仿真结果表明,该补偿器能够有效地消除网络诱导时延变化对控制性能的负面影响;结合该自适应Sm ith补偿器所设计的控制系统能够获得很好的控制性能与较强的鲁棒性. 相似文献
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针对网络时延影响网络控制系统(NCS)性能的问题,提出采用模糊校正来优化广义预测控制的控制效果.该方法降低了广义预测控制的建模误差对一般系统的影响,更好地解决了网络控制中的时延问题,从而可以更好地对系统实行实时控制.采用Matlab对控制系统进行仿真,结果表明,具有模糊校正的广义预测控制,比单一的广义预测控制的控制效果有明显提高. 相似文献
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网络化控制系统(NCSs)是一种通过实时化网络进行数据传输的控制系统.控制系统中的传感器、控制器、执行器等往往通过网络连接起来形成闭环控制系统.然而实际系统中由于带宽限制等客观因素,存在有因网络诱导延迟而引起的系统性能下降问题.考虑了前向通道,反馈通道中同时存在网络诱导时延情况下的网络预测控制(NPC)设计问题,提出了一种新的网络预测控制方法,用以克服网络诱导时延对系统性能带来的影响. 相似文献
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具有通信约束的网络化控制系统容错控制研究 总被引:3,自引:0,他引:3
Implementing a control system over a communication network induces inevitable time delays that may degrade performance and even cause instability. One of the most effective ways to reduce the negative effect of delays on the performance of networked control system (NCS) is to reduce network traffic. In this paper, adjustable deadbands are explored as a solution to reduce network traffic in NCS. A method of fault-tolerant control of networked control system is presented, which takes into account system response as well as network traffic. The integrity design for a kind of NCS with sensor failures and actuator failures is analyzed based on robust fault-tolerant control theory and information scheduling. After detailed theoretical analysis, the paper also provides the simulation results, which further validate the proposed scheme. 相似文献
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Tengli Wang Chuan Zhou Hui Lu Junda He Jian Guo 《International Journal of Control, Automation and Systems》2018,16(1):197-206
A novel co-design scheme of hybrid scheduling strategy, adaptive logarithmic quantizer and dynamic robust H-infinity output feedback controller for a class of networked control system (NCS)with communication constraints and time delay is proposed. The hybrid scheduling scheme integrates dead zone scheduling and Try Once Discard (TOD) scheduling so as to get the stronger adaptability and flexibility than the single scheduling. In this scheme, dead zone scheduling which updates the threshold according to mode-dependent control strategy is used for single node of NCS to reduce the network bandwidth utilization while TOD scheduling is used for the whole node of NCS in order to meet the requirements of communication constraints and guarantee the overall system performance.We develop the integrated design for the hybrid scheduling strategy, adaptive quantizer and dynamic robust output feedback controller to maintain asymptotic stability of the closed-loop NCS by using the multiple-Lyapunov function and switched system theory. The proposed method can improve the the quality of service (QoS) meanwhile ensure the quality of control (QoC) of overall systems, which make a better trade-off between network utilization and control performance. An simulation example demonstrates the efficiency of the proposed method. 相似文献
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基于强化学习的浓密机底流浓度在线控制算法 总被引:1,自引:0,他引:1
复杂过程工业控制一直是控制应用领域研究的前沿问题. 浓密机作为一种复杂大型工业设备广泛用于冶金、采矿等领域. 由于其在运行过程中具有多变量、非线性、高时滞等特点, 浓密机的底流浓度控制技术一直是学界、工业界的研究难点与热点. 本文提出了一种基于强化学习技术的浓密机在线控制算法. 该算法在传统启发式动态规划 (Heuristic dynamic programming, HDP)算法的基础上, 设计融合了评价网络与模型网络的双网结构, 并提出了基于短期经验回放的方法用于增强评价网络的训练准确性, 实现了对浓密机底流浓度的稳定控制, 并保持控制输入稳定在设定范围之内. 最后, 通过浓密机仿真实验的方式验证了算法的有效性, 实验结果表明本文提出的方法在时间消耗、控制精度上优于其他算法. 相似文献
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A multi‐variable direct self‐organizing fuzzy neural network control (M‐DSNNC) method is proposed for the multi‐variable control of the wastewater treatment process (WWTP). In this paper, the proposed control system is an essential multi‐variable control method for the WWTP. No exact plant model is required, which avoids the difficulty of establishing the mathematics model of WWTP. The M‐DSNNC system is comprised of a fuzzy neural network controller and a compensation controller. The fuzzy neural network is used for approximating the ideal control law under a general nonlinear system. Moreover, the neural network is designed in a self‐organizing mode to adapt the uncertainty environment. Simulation results, based on the international benchmark simulation model No.1 (BSM1), demonstrate that the control accuracy is improved under the proposed M‐DSNNC method, and the controller has a much stronger decoupling ability. 相似文献
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一种基于时间差分算法的神经网络预测控制系统 总被引:5,自引:0,他引:5
为提高多步预测控制的计算效率,提出一种基于时间差分算法的Elman网络多步预测控制器的设计方法.用Elman网络对非线性系统输出值进行直接多步预估,并针对BP算法无法对网络权值的实时调整进行渐进计算的缺点,提出了将时间差分法和BP算法相结合的新的网络学习算法;为简化计算,采用单值预测控制算法对非线性系统进行滚动优化以实现对下一步控制量的优化计算.理论分析与仿真结果表明,该方法具有结构简单、运算量小、速度快的特点,可应用于实时快速系统,并且对系统参数的变化具有一定的自适应性. 相似文献
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传统的氨法脱硫控制系统存在延迟时间较长、无法实现实时跟踪负荷的局限性。针对该问题提出的Smith预估补偿装置,通过抵消系统中的纯滞后环节来提高控制系统的实时性。虽然该方法有效解决了长延时问题,但系统中PID参数调整采用的是试错法并依赖于调试操作经验,偶然性和因人而异导致系统波动较大。本文提出了BP(back propagation)神经网络的PID参数整定方法,该方法能实现对任意非线性函数的逼近,通过神经网络学习得到最佳的比例、微分、积分系数组合。运用该方法建模并进行长时过程控制仿真,结果验证了算法的可行性,其误差小,大幅提高了氨法脱硫系统的实时性和稳定性,实现了智能化精准控制效果。 相似文献
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A wireless sensor network (WSN) is an application area that is valuable in various fields, such as healthcare monitoring, environmental monitoring, and so on. Application areas require WSNs with high throughput and low degree of packet loss. Due to congestion in the network, the throughput of the network is affected, which imposes the need for congestion control in the network. This article proposes a method, titled NARX Neural network-based Rate Adjustment (NNRA) for avoiding and controlling congestion in the network. Initially, congestion in the network is avoided by dropping packets and the NNRA is used to control congestion in the network when congestion is present. Performance analysis is carried out in terms of throughput, delay, size of the queue, packet loss, and the level of the congestion using two setups. The results of the proposed method are compared with the existing methods to prove the effectiveness of the proposed method. The proposed method attained a maximum throughput at a rate of 0.9585 and minimum values for delay, queue size, packet loss, and the congestion level. 相似文献