• Model predictive control was applied to solve the dynamic optimization problems of the inventory in supply chain management for the demand uncertainty of supply chain under networked manufacturing.

    针对网络化制造环境下供应链需求不确定的特点,采用模型预测控制技术解决供应链管理中库存的动态优化问题。

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  • A robust model predictive control (MPC) scheme based on fuzzy modelling is proposed for a nonlinear system.

    针对离散不确定模糊模型,提出了一种鲁棒非线性模型预测控制方法。

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  • An important advantage of model predictive control (MPC) is its ability to cope with constraints on controls and states in an explicit and optimal way.

    模型预测控制的一个主要优点是能显式并优化处理控制量和状态量的约束。

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  • Since 1970's, model predictive control (MPC), which has advantage of good robustness and easily modeling, has widely applied in the industry.

    预测控制自上世纪70年代产生以来,因其对模型要求低、具有较强鲁棒性等特点,在生产过程中获得了广泛的应用。

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  • Based on model predictive control techniques, MCC is a multivariable constrained optimal controller with easy task switching.

    基于模型预测控制技术的MCC是一种带有约束、多变量和灵活控制任务切换的优化控制器。

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  • The design method based on nonlinear model predictive control is put forward, and analytical solutions are drawn from it.

    提出基于非线性模型预测控制的快速汽门控制器设计方法并推导出控制规律解析式。

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  • One of the limitations of model predictive control (MPC) is that the control action is very slow when immeasurable disturbances exist, especially when slop disturbance exists.

    模型预测控制在处理不可测干扰时有明显的局限性,特别是对于类似斜坡一样的干扰,控制作用十分缓慢。

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  • A good control system should not only ensure stability of system and safety of production, but also can bring economic benefit when a model predictive control technique is taken into effect.

    在实施模型预测控制技术的过程中,一个良好的控制系统不但要保证系统的稳定性和生产的安全性,还要带来一定的经济效益。

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  • Aiming at characteristics of dynamic supply chain management under networked manufacturing, distributed model predictive control was applied to solve dynamic optimization control in supply chain.

    针对网络化制造环境下动态供应链管理特点,利用分布式模型预测控制技术解决供应链中动态优化控制问题。

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  • By applying multivariable model predictive control (MPC) technology, the control performance of the gasoline debutanizer of fluid catalytic cracking unit can be improved.

    将多变量模型预测控制技术应用于催化裂化汽油稳定塔的控制,有助于提高稳定塔的控制品质。

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  • Based on the strategy of constrained model predictive control, a two degree control system is designed for continuous light tuning of a high pressure sodium lamp.

    结合模型预测控制策略,设计了高压钠灯连续调光二级控制系统。

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  • The simulative results show that the control performance of the model predictive control system is superior to that of the traditional cascade control system.

    仿真结果表明,较之传统的过热汽温串级调节系统,采用该模型预测控制策略的过热汽温控制系统的控制性能有很大的提高。

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  • Model predictive control (MPC) is an example of successful applications of modern control theory in industrial processes.

    模型预测控制(MPC)是现代控制理论在工业过程控制中成功应用的例子。

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  • Model predictive control (MPC) has become one of the most successful advanced control techniques in the chemical and petrochemical industry recently.

    模型预测控制(MPC)是当今石油、化工等工业中应用最为成功的先进控制技术之一。

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  • It is difficult to keep favorable controlling performance of model predictive control (MPC) by linear model due to controlled plant nonlinearity in propylene rectifier.

    在丙烯精馏塔的控制中,由于被控对象的非线性特性,采用线性模型的模型预测控制器难以保持良好的控制性能。

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  • Model predictive control (MPC) refer to a class of control algorithms that optimize the current input by predicting the future behavior of system based on system dynamic model.

    模型预测控制(MPC)是一种根据系统动态模型和历史信息,通过对系统未来行为的预测来优化当前输入的控制策略。

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  • As a computer control algorithm, Model Predictive Control (MFC) has many successful applications in industry control process and has become an important advanced process control strategy.

    模型预测控制作为一种新型计算机控制算法,在工业控制界取得许多成功应用,现已成为一种重要的先进控制策略。

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  • The author comprehensively expatiated on the concept, characteristics of the model predictive control and structural form of the model predictive control system.

    系统全面地阐述了模型预测控制的概念、特点及模型预测控制系统的结构型式。

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  • Firstly, it considers the simple linear model predictive control algorithms.

    首先考虑简单的线性预测控制。

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  • For the uncertain nonlinear system, the multiple-model predictive control is studied which combines the switching method for the nonlinearity and the one for the model uncertainty.

    提出了不确定非线性系统多模型预测控制的新方法,它结合了针对非线性的基于系统输出的切换方法和针对不确定性的模型切换方法。

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  • Model mismatch is a common problem in model predictive control, as well as one of the most important reasons of bad performance.

    模型失配是预测控制中普遍存在的问题,是导致预测控制器性能下降的重要原因。

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  • To solve the problem of perturbation of witching multi-model predictive control, weighted multi-model fuzzy predictive control is put forward.

    为了解决切换多模型预测控制的抖动问题,提出了加权多模型模糊预测控制。

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  • Model predictive control based on the local linearization state-space model is introduced in detail.

    详细的介绍了基于局部线性化状态空间模型的预测控制算法。

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  • Robust model predictive control is proposed for a class of nonlinear systems with constraint inputs based on fuzzy T-S model.

    针对一类基于模糊T-S模型的输入受限非线性系统提出了鲁棒模型预测控制。

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  • Model predictive control the accuracy of the model do not ask for much on the model mismatch, non-minimum phase systems, the impact of uncertain interference robustness, higher performance.

    模型预测控制对模型精度要求不高,对模型失配、非最小相位系统、不确定干扰的影响具有较强的鲁棒性,具有较高的控制性能。

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  • Model predictive control with least squares support vector machine (LS-SVM) has good control performance on the ship course even under the condition of disturbance and model parameter perturbation.

    基于最小二乘支持向量机的船舶航向预测控制系统对外界干扰及模型参数摄动均具有较好的适应能力以及良好的控制性能。

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  • A nonlinear model predictive control (NMPC) strategy based on T_S fuzzy model is proposed.

    提出了一种新的基于T_S模糊模型的非线性预测控制策略。

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  • Furthermore, using a state space model based predictive control algorithm, a multi-composition feedback model predictive control strategy is developed.

    并应用基于状态空间模型的模型预测控制算法,推导了间歇精馏塔多个浓度反馈时的模型预测控制策略。

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  • Two-step model predictive control is applied, which decomposes the MPC problem into a dynamic optimization problem upon linear model and a static rooting problem of nonlinear algebraic equation.

    采用两步法预测控制,即将预测控制问题分解为一基于线性模型的的动态优化问题及一非线性模型的静态求根问题。

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  • Two-step model predictive control is applied, which decomposes the MPC problem into a dynamic optimization problem upon linear model and a static rooting problem of nonlinear algebraic equation.

    采用两步法预测控制,即将预测控制问题分解为一基于线性模型的的动态优化问题及一非线性模型的静态求根问题。

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