针对过程复杂且结构未知的对象,在保证模型有效性的前提下,根据数据信息构建简单模型来简化控制器的求解是亟待解决的问题。以受控自回归模型为例,提出一种基于修正最小角回归算法的稀疏辨识方法。首先将系统模型转化为过参数化的高维...针对过程复杂且结构未知的对象,在保证模型有效性的前提下,根据数据信息构建简单模型来简化控制器的求解是亟待解决的问题。以受控自回归模型为例,提出一种基于修正最小角回归算法的稀疏辨识方法。首先将系统模型转化为过参数化的高维稀疏模型,然后将最小角回归算法用于稀疏系统辨识,并提出绝对角度停止准则,使算法经过少量的迭代即可获得模型的稀疏参数估计,并同时获得有效的时滞和阶次估计。结合辨识得到的受控自回归模型,引入一种基于指定相位点频率和增益的比例-积分-微分(proportional integral derivative,PID)控制器。数值仿真和平衡机器人的姿态控制仿真表明,该稀疏辨识算法在低数据量下具有较高的辨识精度,建立的模型具有较好的泛化性能,控制器具有良好的控制效果。展开更多
The quantum bacterial foraging optimization(QBFO)algorithm has the characteristics of strong robustness and global searching ability. In the classical QBFO algorithm, the rotation angle updated by the rotation gate is...The quantum bacterial foraging optimization(QBFO)algorithm has the characteristics of strong robustness and global searching ability. In the classical QBFO algorithm, the rotation angle updated by the rotation gate is discrete and constant,which cannot affect the situation of the solution space and limit the diversity of bacterial population. In this paper, an improved QBFO(IQBFO) algorithm is proposed, which can adaptively make the quantum rotation angle continuously updated and enhance the global search ability. In the initialization process, the modified probability of the optimal rotation angle is introduced to avoid the existence of invariant solutions. The modified operator of probability amplitude is adopted to further increase the population diversity.The tests based on benchmark functions verify the effectiveness of the proposed algorithm. Moreover, compared with the integerorder PID controller, the fractional-order proportion integration differentiation(PID) controller increases the complexity of the system with better flexibility and robustness. Thus the fractional-order PID controller is applied to the servo system. The tuning results of PID parameters of the fractional-order servo system show that the proposed algorithm has a good performance in tuning the PID parameters of the fractional-order servo system.展开更多
An improved particle swarm algorithm based on the D-Tent chaotic model is put forward aiming at the standard particle swarm algorithm. The convergence rate of the late of proposed algorithm is improved by revising the...An improved particle swarm algorithm based on the D-Tent chaotic model is put forward aiming at the standard particle swarm algorithm. The convergence rate of the late of proposed algorithm is improved by revising the inertia weight of global optimal particles and the introduction of D-Tent chaotic sequence. Through the test of typical function and the autotuning test of proportionalintegral-derivative （PID） parameter, finally a simulation is made to the servo control system of a permanent magnet synchronous motor （PMSM） under double-loop control of rotating speed and current by utilizing the chaotic particle swarm algorithm. Studies show that the proposed algorithm can reduce the iterative times and improve the convergence rate under the condition that the global optimal solution can be got.展开更多
大量新能源并入电网,对水电的运行提出了更高的要求。为了提高水电的调节特性,提出一种考虑综合调节特性的水轮机调速器比例积分微分(proportional integral derivative,PID)控制参数整定方法。首先,基于特征线法和水轮机特性曲线建立...大量新能源并入电网,对水电的运行提出了更高的要求。为了提高水电的调节特性,提出一种考虑综合调节特性的水轮机调速器比例积分微分(proportional integral derivative,PID)控制参数整定方法。首先,基于特征线法和水轮机特性曲线建立了水轮机调节系统模型。其次,基于第三代非支配排序遗传算法(non-dominated sorting genetic algorithmⅢ,NSGA-Ⅲ),以转速的时间乘绝对误差积分准则(integrated time and absolute error,ITAE)和超调量为目标,以比例调节系数,积分调节系数和微分调节系数为决策变量,得到帕雷托(Pareto)解集。最后,基于优劣解距离法(technique for order preference by similarity to ideal solution,TOPSIS),以增减负荷工况下的功率反调,超调量,稳定时间,机组水头极值,转速ITAE和超调量为指标,最终得到综合调节特性最好的PID参数。结果表明:该PID参数整定方法可以有效提升水轮机的综合调节特性,为实际工程中PID参数的选取提供理论依据。展开更多
汽车悬架控制系统是一个由较多非线性因素共同作用的复杂系统,针对传统PID控制效果不理想的问题,通过数值拟合的方式引入弹簧与阻尼等非线性影响因素,建立1/4汽车悬架非线性动力学模型,借鉴免疫反馈原理,结合积分控制的规律,提出一种模...汽车悬架控制系统是一个由较多非线性因素共同作用的复杂系统,针对传统PID控制效果不理想的问题,通过数值拟合的方式引入弹簧与阻尼等非线性影响因素,建立1/4汽车悬架非线性动力学模型,借鉴免疫反馈原理,结合积分控制的规律,提出一种模糊免疫PID(proportion integral derivative)控制方法,并利用免疫进化算法进行参数优化设计。仿真结果表明,该方法在汽车非线性悬架控制系统中可行且有效,其控制器性能也优于常规的PID控制器,具有更好的响应特性,同时也提高了汽车的操作稳定性和乘坐舒适性。展开更多
文摘针对过程复杂且结构未知的对象,在保证模型有效性的前提下,根据数据信息构建简单模型来简化控制器的求解是亟待解决的问题。以受控自回归模型为例,提出一种基于修正最小角回归算法的稀疏辨识方法。首先将系统模型转化为过参数化的高维稀疏模型,然后将最小角回归算法用于稀疏系统辨识,并提出绝对角度停止准则,使算法经过少量的迭代即可获得模型的稀疏参数估计,并同时获得有效的时滞和阶次估计。结合辨识得到的受控自回归模型,引入一种基于指定相位点频率和增益的比例-积分-微分(proportional integral derivative,PID)控制器。数值仿真和平衡机器人的姿态控制仿真表明,该稀疏辨识算法在低数据量下具有较高的辨识精度,建立的模型具有较好的泛化性能,控制器具有良好的控制效果。
基金supported by the National Natural Science Foundation of China(6137415361473138)+2 种基金Natural Science Foundation of Jiangsu Province(BK20151130)Six Talent Peaks Project in Jiangsu Province(2015-DZXX-011)China Scholarship Council Fund(201606845005)
文摘The quantum bacterial foraging optimization(QBFO)algorithm has the characteristics of strong robustness and global searching ability. In the classical QBFO algorithm, the rotation angle updated by the rotation gate is discrete and constant,which cannot affect the situation of the solution space and limit the diversity of bacterial population. In this paper, an improved QBFO(IQBFO) algorithm is proposed, which can adaptively make the quantum rotation angle continuously updated and enhance the global search ability. In the initialization process, the modified probability of the optimal rotation angle is introduced to avoid the existence of invariant solutions. The modified operator of probability amplitude is adopted to further increase the population diversity.The tests based on benchmark functions verify the effectiveness of the proposed algorithm. Moreover, compared with the integerorder PID controller, the fractional-order proportion integration differentiation(PID) controller increases the complexity of the system with better flexibility and robustness. Thus the fractional-order PID controller is applied to the servo system. The tuning results of PID parameters of the fractional-order servo system show that the proposed algorithm has a good performance in tuning the PID parameters of the fractional-order servo system.
基金supported by the National Natural Science Foundation of China(61301011)the Fundamental Research Funds for the Central Universities(HIT.NSRIF.2012010)+1 种基金the China Postdoctoral Science Foundation(2013M540279)the Heilongjiang Postdoctoral Financial Assistance(LBH-Z11157)
文摘An improved particle swarm algorithm based on the D-Tent chaotic model is put forward aiming at the standard particle swarm algorithm. The convergence rate of the late of proposed algorithm is improved by revising the inertia weight of global optimal particles and the introduction of D-Tent chaotic sequence. Through the test of typical function and the autotuning test of proportionalintegral-derivative （PID） parameter, finally a simulation is made to the servo control system of a permanent magnet synchronous motor （PMSM） under double-loop control of rotating speed and current by utilizing the chaotic particle swarm algorithm. Studies show that the proposed algorithm can reduce the iterative times and improve the convergence rate under the condition that the global optimal solution can be got.
基金Supported by National Natural Science Foundation of China （61273260）, Specialized Research Fund for the Doctoral Program of Higher Education of China （20121333120010）, Natural Scientific Research Foundation of the Higher Education Institutions of Hebei Province （2010t65）, the Major Program of the National Natural Science Foundation of China （61290322）, Foundation of Key Labora- tory of System Control and Information Processing, Ministry of Education （SCIP2012008）, and Science and Technology Research and Development Plan of Qinhuangdao City （2012021A041）
文摘大量新能源并入电网,对水电的运行提出了更高的要求。为了提高水电的调节特性,提出一种考虑综合调节特性的水轮机调速器比例积分微分(proportional integral derivative,PID)控制参数整定方法。首先,基于特征线法和水轮机特性曲线建立了水轮机调节系统模型。其次,基于第三代非支配排序遗传算法(non-dominated sorting genetic algorithmⅢ,NSGA-Ⅲ),以转速的时间乘绝对误差积分准则(integrated time and absolute error,ITAE)和超调量为目标,以比例调节系数,积分调节系数和微分调节系数为决策变量,得到帕雷托(Pareto)解集。最后,基于优劣解距离法(technique for order preference by similarity to ideal solution,TOPSIS),以增减负荷工况下的功率反调,超调量,稳定时间,机组水头极值,转速ITAE和超调量为指标,最终得到综合调节特性最好的PID参数。结果表明:该PID参数整定方法可以有效提升水轮机的综合调节特性,为实际工程中PID参数的选取提供理论依据。
文摘汽车悬架控制系统是一个由较多非线性因素共同作用的复杂系统,针对传统PID控制效果不理想的问题,通过数值拟合的方式引入弹簧与阻尼等非线性影响因素,建立1/4汽车悬架非线性动力学模型,借鉴免疫反馈原理,结合积分控制的规律,提出一种模糊免疫PID(proportion integral derivative)控制方法,并利用免疫进化算法进行参数优化设计。仿真结果表明,该方法在汽车非线性悬架控制系统中可行且有效,其控制器性能也优于常规的PID控制器,具有更好的响应特性,同时也提高了汽车的操作稳定性和乘坐舒适性。
