SBIR Phase II: Neural Networks, Youla Parameterization and Reconfigurable Control Systems

9321264赛克斯这个项目将开发一种混合频域/神经控制算法，通过使用神经网络技术来调整“友拉设计参数”。这样产生的控制器保证是稳定的，并且可以实现任何和/或干扰抑制、极点配置、鲁棒跟踪和/或干扰抑制、同时设计、初值设计等。神经控制固有的自适应性和鲁棒性被集成到频域控制器中。强大的(本体)神经网络训练技术可以在控制系统设计问题上发挥作用，使人们能够设计控制器，而不需要事先限制控制器的阶数。开发了一种可重新配置的控制体系结构，其中控制器被训练以处理多种情况；飞行控制器的可选轨迹、机器人手臂上的变化负载、电源中的交流电流波形等；在必要时通过训练集来推广到新的控制器。该方法直接适用于线性多变量系统，并可通过将Youla参数化法推广到非线性情形而推广。*v S t disturbanceintegratedetc.generalizingscenariosbeyondextendiblevariousB C D E F G I N O P Q R S T U V W X Y Z‘a b g h S j k L m n r S t u v w x y z{}~9321264赛克斯这个项目将开发一种混合频域/神经控制算法，利用神经网络技术来实现。=H R V b k Q{)。$(F/.$。1倍符号“Helvetica 5 Courier New E O Y‘=H N R 4 V C b U kQ{，“Hj2%9E(S R：\WW20USER\ABSTRACT.DOT摘要艾丽西亚·E·哈里斯艾丽西亚·E·哈里斯

9321264 Saeks This project will develop a hybrid frequency domain/neurocontrol algorithm by using neural network techniques to adjust the "Youla design parameter." This yields a controller which is guaranteed to be stable and can implement any of and /or distrubance rejection, pole placement, robust tracking and/or disturbance rejection, simultaneous design, initial value design, etc. The adaptivity and robustness intrinsic to neurocontrol is integerated into the frequency domain controller. Powerful (ontogenic) neural network training techniques may be brought to bare on the control system design problem allowing one to design a controller without a prior restrictions on its order. A reconfigurable control architecture is developed where the controller is trained to deal with multiple scenarios; alternative trajectories for a flight controller, varying loads on a robot arm, alternative current waveshapes in a power supply, etc; generaliziang to new scencarios byond the training set where necessary. The approach is directly applicable to linear multivariate systems and extendable, via the vairous generalizations of the Youla parameterization to the nonlinear case. *** v s t disturbanceintegratedetc.generalizingscenariosbeyondextendiblevariousB C D E F G I N O P Q R S T U V W X Y Z \ ^ _ ` a b g h S j k l m n r s t u v w x y z { } ~ 9321264 Saeks This project will develop a hybrid frequency domain/neurocontrol algorithm by using neural net work techniques to . = H R V b k q { ) . $ ( F / . $ . 1 Times Symbol " Helvetica 5 Courier New E O Y ` = H N R 4 V C b U k q { , " h j2 % 9 E ( S R:\WW20USER\ABSTRACT.DOT abstract Alicia E. Harris Alicia E. Harris