Nonlinear model predictive controllers(NMPC)can predict the future behavior of the under-controlled system using a nonlinear predictive model.Here,an array of hyper chaotic diagonal recurrent neural network(HCDRNN)was...Nonlinear model predictive controllers(NMPC)can predict the future behavior of the under-controlled system using a nonlinear predictive model.Here,an array of hyper chaotic diagonal recurrent neural network(HCDRNN)was proposed for modeling and predicting the behavior of the under-controller nonlinear system in a moving forward window.In order to improve the convergence of the parameters of the HCDRNN to improve system’s modeling,the extent of chaos is adjusted using a logistic map in the hidden layer.A novel NMPC based on the HCDRNN array(HCDRNN-NMPC)was proposed that the control signal with the help of an improved gradient descent method was obtained.The controller was used to control a continuous stirred tank reactor(CSTR)with hard-nonlinearities and input constraints,in the presence of uncertainties including external disturbance.The results of the simulations show the superior performance of the proposed method in trajectory tracking and disturbance rejection.Parameter convergence and neglectable prediction error of the neural network(NN),guaranteed stability and high tracking performance are the most significant advantages of the proposed scheme.展开更多
针对长时间充放电后锂电池模组之间荷电状态(state of charge,SOC)不一致的问题,传统集中式均衡电路存在均衡速度过低的缺陷,以对称式开关阵列、Boost变换器与LC准谐振电路作为均衡主电路,提出了一种基于连续集模型预测控制(continuous ...针对长时间充放电后锂电池模组之间荷电状态(state of charge,SOC)不一致的问题,传统集中式均衡电路存在均衡速度过低的缺陷,以对称式开关阵列、Boost变换器与LC准谐振电路作为均衡主电路,提出了一种基于连续集模型预测控制(continuous control set model predictive control,CCS-MPC)的均衡控制策略。首先,对均衡系统进行建模,构建离散状态空间方程;然后,根据状态方程设计多步模型预测算法,并以SOC预测值和参考值、变换器开关管当前输入和上一时刻输入之间的误差作为价值函数;最后,对价值函数进行二次规划,在线求解出一组控制最优解,并应用于均衡系统,通过动态调整占空比以控制均衡电流的大小。相较于单步预测,多步预测需要考虑被控量在多个周期内保持最优,可以保证在每个均衡周期内均衡器都能输出最优的均衡电流,有效防止均衡器失稳。仿真结果表明,所提模型预测算法实现了各电池组SOC一致,保证了均衡电流的稳定输出,相比常规PI算法缩短了17%的均衡时间。展开更多
针对具有强非线性、时变、有纯滞后等综合复杂性的连续搅拌釜(continuous stirred tank reactor,CSTR)反应过程,把无限时域鲁棒二次目标函数进行分解,构成新目标函数,并允许未来控制序列的第1个控制量作为自由决策变量的方式,提出了一...针对具有强非线性、时变、有纯滞后等综合复杂性的连续搅拌釜(continuous stirred tank reactor,CSTR)反应过程,把无限时域鲁棒二次目标函数进行分解,构成新目标函数,并允许未来控制序列的第1个控制量作为自由决策变量的方式,提出了一种非线性鲁棒模型预测控制方法,从而提高了算法的通用性,改善系统的性能。通过连续搅拌釜的实验研究,实验结果说明了所提算法的有效性。展开更多
文摘Nonlinear model predictive controllers(NMPC)can predict the future behavior of the under-controlled system using a nonlinear predictive model.Here,an array of hyper chaotic diagonal recurrent neural network(HCDRNN)was proposed for modeling and predicting the behavior of the under-controller nonlinear system in a moving forward window.In order to improve the convergence of the parameters of the HCDRNN to improve system’s modeling,the extent of chaos is adjusted using a logistic map in the hidden layer.A novel NMPC based on the HCDRNN array(HCDRNN-NMPC)was proposed that the control signal with the help of an improved gradient descent method was obtained.The controller was used to control a continuous stirred tank reactor(CSTR)with hard-nonlinearities and input constraints,in the presence of uncertainties including external disturbance.The results of the simulations show the superior performance of the proposed method in trajectory tracking and disturbance rejection.Parameter convergence and neglectable prediction error of the neural network(NN),guaranteed stability and high tracking performance are the most significant advantages of the proposed scheme.
文摘针对长时间充放电后锂电池模组之间荷电状态(state of charge,SOC)不一致的问题,传统集中式均衡电路存在均衡速度过低的缺陷,以对称式开关阵列、Boost变换器与LC准谐振电路作为均衡主电路,提出了一种基于连续集模型预测控制(continuous control set model predictive control,CCS-MPC)的均衡控制策略。首先,对均衡系统进行建模,构建离散状态空间方程;然后,根据状态方程设计多步模型预测算法,并以SOC预测值和参考值、变换器开关管当前输入和上一时刻输入之间的误差作为价值函数;最后,对价值函数进行二次规划,在线求解出一组控制最优解,并应用于均衡系统,通过动态调整占空比以控制均衡电流的大小。相较于单步预测,多步预测需要考虑被控量在多个周期内保持最优,可以保证在每个均衡周期内均衡器都能输出最优的均衡电流,有效防止均衡器失稳。仿真结果表明,所提模型预测算法实现了各电池组SOC一致,保证了均衡电流的稳定输出,相比常规PI算法缩短了17%的均衡时间。
文摘针对具有强非线性、时变、有纯滞后等综合复杂性的连续搅拌釜(continuous stirred tank reactor,CSTR)反应过程,把无限时域鲁棒二次目标函数进行分解,构成新目标函数,并允许未来控制序列的第1个控制量作为自由决策变量的方式,提出了一种非线性鲁棒模型预测控制方法,从而提高了算法的通用性,改善系统的性能。通过连续搅拌釜的实验研究,实验结果说明了所提算法的有效性。
