无线网络状态空间模型约束预测控制仿真

Simulation of State Space Model Constrained Predictive Control for Wireless Network

为了解决无线网络中出现的网络拥塞和数据碰撞等现象,需要对无线网络的预测控制方法进行研究。采用当前预测控制方法对无线网络中的数据进行预测控制时,存在抗干扰性差和预测控制结果精准度低的问题。在状态空间模型的基础上提出一种无线网络预测控制方法,选用状态空间模型作为预测模型,并对状态空间模型进行离散化处理,对离散后的状态空间模型做增量运算,得到无线网络增广状态空间模型。根据无线网络增广状态空间模型得到受控自回归积分滑动平均模型,采用Diophantine方程对性能指标函数进行改写,根据性能指标的计算结果得到无线网络的预测控制率,对预测控制结果进行反馈校正,完成无线网络的预测控制。仿真结果表明,所提方法的抗干扰性强、预测结果精准度高。

On the basis of state space model,a predictive control method for wireless network was proposed.At first,the state space model wag chosen as the predictive mode,and the state space model was discretized.Then,the state space model after the discretization was incrementally operated to obtain the augmented state space model of wireless network.Based on the augmented siate space model of wireless network,the controlled auto-regressive integrated moving average was obtained.The Diophantine equation was used to rewrite the performance index function. Moreover,the predictive control rate of wireless network was obtained based on the calculation result of performance index.Finally,feedback correction was performed on prediction control result to complete the predictive control of wireless network.Simulation results show that the proposed method has strong anti-interference and high accuracy of prediction resu1ts.