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扰动模型的准确性对模型预测控制算法的扰动抑制能力有重要影响,当前模型预测控制广泛采用的阶跃扰动模型不能准确描述进入系统的不可测扰动,扰动抑制能力有限.自适应扰动模型可以较好的描述不可测扰动,提高对扰动的预估和抑制能力.本文对采用自适应时间序列扰动模型的预测控制进行分析,研究了扰动自适应预测控制(DMCA)的闭环结构以及带宽、灵敏度函数等频域指标与控制器抗扰性能的关系.带宽大的系统抑制扰动的速度快,灵敏度函数幅值越小则对扰动的抑制能力越强.理论分析和仿真结果表明与动态矩阵控制(DMC)相比,采用自适应扰动模型的DMCA算法能够更好的预测和抑制扰动,被控变量偏离设定值的最大幅度降低60%,带宽是DMC的1.5倍、调节速度更快,在低频段有较小的灵敏度函数值.自适应扰动模型提升了DMCA控制器的扰动抑制性能,对保障系统安全平稳运行和增加效益有重要意义. 相似文献
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针对于一类具有强耦合、负载不确定性和外界干扰的永磁同步电机(PMSM)系统,本文研究了基于无模型自适应预测控制(MFAPC)问题,并提出了一种新颖的MFAPC方案来实现有外界扰动的PMSM系统的速度追踪任务.所提出控制方案的主要优势在于仅使用了被控系统的输入/输出数据,并且对外界干扰具有较强的鲁棒性.此外,还讨论了闭环系统跟踪误差的收敛性以及有界输入有界输出的稳定性.最后,通过与传统的PI控制方案、原型无模型自适应控制(MFAC)方案的仿真结果相比较,验证了所提出MFAPC方案的有效性和优越性. 相似文献
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利用多个固定模型(或元素模型)来逼近含未知参数的被控系统,基于每一个元素模型建立最优控制器,并由各局部模型控制器的加权和构成被控系统的控制器。对于这种多模型自适应控制器,在每一个采样时刻,每一个元素模型的权值将由遗传算法计算得出。仿真结果表明,采用该文提出的控制器,当被控对象的模型参数剧烈变化时系统输出依然可以很好地跟踪设定值。 相似文献
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基于极点配置的多模型自适应控制 总被引:2,自引:0,他引:2
基于极点配置技术对单输入单输出离散时间被控对象提出多模型自适应控制算法,在保证稳定性的前提下,算法对被控对象参数跳变时能进行有效的控制,并提高了系统的瞬态响应。 相似文献
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基于可行模型集合方法的多模型切换控制 总被引:1,自引:0,他引:1
对含参数跳变的一类具有有界干扰的多输入多输出系统,为改善系统的瞬态响应性能,采用由多个固定模型和两个自适应模型组成的多模型,并引入切换指标函数构成多模型切换控制器。为克服多模型方法计算量大的缺点,采用可行模型集合方法,给出了可行模型应满足的必要条件。应用这一必要条件,对系统的多个模型进行检验,可快速缩小模型可行集合的范围,再通过切换指标函数,在可行模型集合中选择正确的控制器,从而在不降低系统响应性能的前提下,提高计算速度。 相似文献
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This paper addresses the problems of disturbance estimation and anti‐disturbance control for nonlinear system with exogenous disturbance, which is generated from an unknown exogenous system. The state observer and the adaptive disturbance observer are designed, simultaneously. Compared with the existing methods, which assumed that the exogenous system parameter matrix was known, our disturbance observer is more applicable in practice. Utilizing the estimation information, an observer‐based dynamic output feedback controller is designed, which avoids the influence of output disturbance on the closed‐loop system, and contains a disturbance compensation term to compensate the input disturbance. Finally, simulations are provided to demonstrate the effectiveness of the proposed approach. Copyright © 2016 John Wiley & Sons, Ltd. 相似文献
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Masahiro Ohshima Hiromu Ohno Iori Hashimoto Mikiro Sasajima Masayuki Maejima Keiichi Tsuto Tadaharu Ogawa 《Journal of Process Control》1995,5(1)
This paper describes the results of a joint university-industry study to control a fatty acid distillation sequence, which is plagued with severe disturbance problems. In order to solve the disturbance problem, a model predictive control algorithm is modified in terms of disturbance prediction. Assuming that the dynamics of the unmeasured disturbances is generated by an auto-regressive form, the dynamics of the disturbance can be adaptively identified by using time series data of prediction errors and inputs. Using an identified disturbance model with a process model, future outputs are predicted. Control actions are determined so that the predicted output is as close to the target value as possible. This modified model predictive control aglorithm is applied to a ratio control scheme for three distillation columns. The control system developed has been in use sucessfully for more than six years to produce commercial products. 相似文献
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为解决一类带干扰的不确定非线性系统中存在的两类未知项——未知函数和外界干扰,采用了直接自适应神经网络控制方法设计控制器。控制器设计中利用径向基函数神经网络良好的逼近性来近似未知函数,利用非线性衰减项来抑制干扰。所用方法结构简单、算法简洁,在一定条件下稳定性和收敛性能定性地得到保证。最后,仿真结果证明了该方法是正确的。 相似文献
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The output feedback robust model predictive control (MPC), for the linear parameter varying (LPV) system with norm-bounded disturbance, is addressed, where the model parametric matrices are only known to be bounded within a polytope. The previous techniques of norm-bounding technique, quadratic boundedness (QB), dynamic output feedback, and ellipsoid (true-state bound; TSB) refreshment formula for guaranteeing recursive feasibility, are fused into the newly proposed approaches. In the notion of QB, the full Lyapunov matrix is applied for the first time in this context. The single-step dynamic output feedback robust MPC, where the infinite-horizon control moves are parameterised as a dynamic output feedback law, is the main topic of this paper, while the multi-step method is also suggested. In order to strictly guarantee the physical constraints, the outer bound of the true state replaces the true state itself, so tightness of this bound has a major effect on the control performance. In order to tighten the TSB, a procedure for refreshing the real-time ellipsoid based on that of the last sampling instant is given. This paper is conclusive for the past results and far-reaching for the future researches. Two benchmark examples are given to show the effectiveness of the novel results. 相似文献
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This paper proposes a new adaptive feedforward cancellation (AFC) control that achieves periodic tracking and/or periodic disturbance rejection. The new control design is a direct scheme in the sense that it adaptively updates the desired control without estimating the unknown disturbance. The proposed new control has several advantages. First, its adaptation gain can be arbitrarily chosen without upsetting the system stability. Second, it can be applied to not only minimum‐phase systems, but also non‐minimum phase systems. Finally, it is shown that the proposed AFC control is independent of where the disturbance enters the system. Copyright © 2011 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society 相似文献