α-β跟踪滤波器具有结构简单、计算方便等优点,在工程中得到了广泛应用,但同时由于参数固定而无法适用于机动场景中的目标跟踪。针对该问题,文章将单神经元自适应PSD(Proportion Sum Differential)算法与α-β滤波相结合。改进后的α-...α-β跟踪滤波器具有结构简单、计算方便等优点,在工程中得到了广泛应用,但同时由于参数固定而无法适用于机动场景中的目标跟踪。针对该问题,文章将单神经元自适应PSD(Proportion Sum Differential)算法与α-β滤波相结合。改进后的α-β滤波算法利用单神经元PSD算法的自适应参数调整能力,根据系统跟踪误差实时调整滤波器参数,因而能够跟踪机动目标。仿真和实测数据处理结果表明,改进的α-β滤波算法能够有效应对目标机动,形成稳定航迹,跟踪性能优于Kalman滤波。展开更多
Taking three-phase electrode adjusting system of submerged arc furnace as study object which has nonlinear, time-variant, multivariable and strong coupling features, a neural adaptive PSD(proportion, sum and different...Taking three-phase electrode adjusting system of submerged arc furnace as study object which has nonlinear, time-variant, multivariable and strong coupling features, a neural adaptive PSD(proportion, sum and differential) dispersive decoupling controller was developed by combining neural adaptive PSD algorithm with dispersive decoupling network. In this work, the production technology process and control difficulties of submerged arc furnace were simply introduced, the necessity of establishing a neural adaptive PSD dispersive decoupling controller was discussed, the design method and the implementation steps of the controller are expounded in detail, and the block diagram of the controlled system is presented. By comparison with experimental results of the conventional PID controller and the adaptive PSD controller, the decoupling ability, adaptive ability, self-learning ability and robustness of the neural adaptive PSD dispersive decoupling controller have been testified effectively. The controller is applicable to the three-phase electrode adjusting system of submerged arc furnace, and it will play an important role for achieving the power balance of three-phrase electrodes, saving energy and reducing consumption in the process of smelting.展开更多
文摘α-β跟踪滤波器具有结构简单、计算方便等优点,在工程中得到了广泛应用,但同时由于参数固定而无法适用于机动场景中的目标跟踪。针对该问题,文章将单神经元自适应PSD(Proportion Sum Differential)算法与α-β滤波相结合。改进后的α-β滤波算法利用单神经元PSD算法的自适应参数调整能力,根据系统跟踪误差实时调整滤波器参数,因而能够跟踪机动目标。仿真和实测数据处理结果表明,改进的α-β滤波算法能够有效应对目标机动,形成稳定航迹,跟踪性能优于Kalman滤波。
基金Project(61174132) supported by the National Natural Science Foundation of ChinaProject(09JJ6098) supported by the Natural Science Foundation of Hunan Province, China
文摘Taking three-phase electrode adjusting system of submerged arc furnace as study object which has nonlinear, time-variant, multivariable and strong coupling features, a neural adaptive PSD(proportion, sum and differential) dispersive decoupling controller was developed by combining neural adaptive PSD algorithm with dispersive decoupling network. In this work, the production technology process and control difficulties of submerged arc furnace were simply introduced, the necessity of establishing a neural adaptive PSD dispersive decoupling controller was discussed, the design method and the implementation steps of the controller are expounded in detail, and the block diagram of the controlled system is presented. By comparison with experimental results of the conventional PID controller and the adaptive PSD controller, the decoupling ability, adaptive ability, self-learning ability and robustness of the neural adaptive PSD dispersive decoupling controller have been testified effectively. The controller is applicable to the three-phase electrode adjusting system of submerged arc furnace, and it will play an important role for achieving the power balance of three-phrase electrodes, saving energy and reducing consumption in the process of smelting.
