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| 基于关联存储网络的非线性约束监督预测控制 | |
| 引用本文： | 刘向杰,牛丽霞,何文广.基于关联存储网络的非线性约束监督预测控制[J].控制与决策,2010,25(8):1230-1236. |
| 作者姓名： | 刘向杰 牛丽霞 何文广 |
| 作者单位： | 1. 华北电力大学控制与计算机工程学院,北京,102206 2. 北京广利核系统工程有限公司,北京,100084 3. 内蒙古大唐国际托克托发电有限责任公司,内蒙古,010000 |
| 基金项目： | 国家自然科学基金项目,新世纪优秀人才支持计划项目 |
| 摘 要： | 设定值优化是复杂工业过程中一种有效的优化控制手段,通过在通常的校正级上面加一层监督级而实现.模型预测控制已广泛应用于工业过程控制,但约束优化的实现是一个难题.鉴于此,建立了非线性监督预测控制的模糊神经网络模型,由此推导出监督预测控制的可行解,并用于燃气轮机系统转速和功率的控制.仿真结果表明了该方法的优越性. |
| 关 键 词： | 多变量监督预测控制 模糊神经网络 约束 燃气轮机 |
| 收稿时间： | 2009/7/22 0:00:00 |
| 修稿时间： | 2009/10/16 0:00:00 |
Constraint multivariable nonlinear supervisory predictive control using associate memory network |
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| LIU Xiang-jie,NIU Li-xia,HE Wen-guang.Constraint multivariable nonlinear supervisory predictive control using associate memory network[J].Control and Decision,2010,25(8):1230-1236. | |
| Authors: | LIU Xiang-jie NIU Li-xia HE Wen-guang |
| Abstract: | The set-point optimization is an effective way of optimal control for complex industrial process, which can be realized by adding a supervisory optimal level without modifying the regulatory level. While model predictive control has been widely used in industrial process, incorporating of constraints is a major problem. Therefore, neuro-fuzzy networks(NFNs) with nonlinear constraint predictive control is presented, and the feasible solution is derived. Power and velocity control of gas turbine in combined cycling boiler is presented to illustrate the implementation and the performance of the proposed method. Simulation results show the superiority of the method. |
| Keywords: | Supervisory predictive control|Neuro-fuzzy networks|Constraint|Gas turbine |
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