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1. 发明授权

US06757570B1 System and method for adaptive control of uncertain nonlinear processes 失效
标题翻译：不确定非线性过程的自适应控制系统和方法
公开(公告)号：US06757570B1
公开(公告)日：2004-06-29
申请号：US09585105
申请日：2000-05-31
申请人： Anthony J. Calise , Byoung-Soo Kim , J. Eric Corban
发明人： Anthony J. Calise , Byoung-Soo Kim , J. Eric Corban
IPC分类号： G05B1302
CPC分类号： G05B13/027 , G05D1/0825
摘要： A process and neural network architecture for on-line adjustment of the weights of the neural network in a manner that corrects errors made by a nonlinear controller designed based on a model for the dynamics of a process under control. A computer system is provided for controlling the dynamic output response signal of a nonlinear physical process, where the physical process is represented by a fixed model of the process. The computer system includes a controlled device for responding to the output response signal of the system. The computer system also includes a linear controller for providing a pseudo control signal that is based on the fixed model for the process and provides a second controller, connected to the linear controller, for receiving the pseudo control signal and for providing a modified pseudo control signal to correct for the errors made in modeling the nonlinearities in the process. A response network is also included as part of the computer system. The response network receives the modified pseudo control signal and provides the output response signal to the controlled device. The second controller preferably is a neural network. The computer system may include a plurality of neural networks with each neural network designated to control a selected variable or degree of freedom within the system.
摘要翻译：一种过程和神经网络架构，用于以校正由基于控制的过程的动力学的模型设计的非线性控制器所做的错误的方式在线调整神经网络的权重。提供了一种用于控制非线性物理过程的动态输出响应信号的计算机系统，其中物理过程由该过程的固定模型表示。计算机系统包括用于响应系统的输出响应信号的受控设备。计算机系统还包括线性控制器，用于提供基于该过程的固定模型的伪控制信号，并提供连接到线性控制器的第二控制器，用于接收伪控制信号并提供经修改的伪控制信号以纠正在过程中对非线性建模的错误。响应网络也作为计算机系统的一部分。响应网络接收修改后的伪控制信号，并向受控设备提供输出响应信号。第二控制器优选地是神经网络。计算机系统可以包括多个神经网络，每个神经网络被指定用于控制系统内的选定变量或自由度。

2. 发明授权

US07415311B2 System and method for adaptive control of uncertain nonlinear processes 失效
标题翻译：不确定非线性过程的自适应控制系统和方法
公开(公告)号：US07415311B2
公开(公告)日：2008-08-19
申请号：US11620032
申请日：2007-01-04
申请人： Anthony J. Calise , Byoung-Soo Kim , J. Eric Corban
发明人： Anthony J. Calise , Byoung-Soo Kim , J. Eric Corban
IPC分类号： G05B13/02 , G06E1/00 , G06E3/00 , G06G7/00
CPC分类号： G05B13/027 , G05D1/0825
摘要： A computer system for controlling a nonlinear physical process. The computer system comprises a linear controller and a neural network. The linear controller receives a command signal for control of the nonlinear physical process and a measured output signal from the output of the nonlinear physical process. The linear controller generates a control signal based on the command signal, a measured output signal, and a fixed linear model for the process. The neural network receives the control signal from the linear controller and the measured output signal from the output of the nonlinear physical process. The neural network uses the measured output signal to modify the connection weights of the neural network. The neural network also generates a modified control signal supplied to the linear controller to iterate a fixed point solution for the modified control signal used to control the nonlinear physical process.
摘要翻译：一种用于控制非线性物理过程的计算机系统。计算机系统包括线性控制器和神经网络。线性控制器接收用于控制非线性物理过程的命令信号和来自非线性物理过程的输出的测量输出信号。线性控制器基于命令信号，测量输出信号和用于该过程的固定线性模型产生控制信号。神经网络接收来自线性控制器的控制信号和来自非线性物理过程的输出的测量输出信号。神经网络使用测量的输出信号来修改神经网络的连接权重。神经网络还生成提供给线性控制器的修改的控制信号，以迭代用于控制非线性物理过程的修改的控制信号的固定点解。

3. 发明授权

US6092919A System and method for adaptive control of uncertain nonlinear processes 失效
标题翻译：不确定非线性过程的自适应控制系统和方法
公开(公告)号：US6092919A
公开(公告)日：2000-07-25
申请号：US510055
申请日：1995-08-01
申请人： Anthony J. Calise , Byoung-Soo Kim
发明人： Anthony J. Calise , Byoung-Soo Kim
IPC分类号： G05B13/02
CPC分类号： G05B13/027 , G05D1/0825
摘要： A process and neural network architecture for on-line adjustment of the weights of the neural network in a manner that corrects errors made by a nonlinear controller designed based on a model for the dynamics of a process under control. A computer system is provided for controlling the dynamic output response signal of a nonlinear physical process, where the physical process is represented by a fixed model of the process. The computer system includes a controlled device for responding to the output response signal of the system. The computer system also includes a linear controller for providing a pseudo control signal that is based on the fixed model for the process and provides a second controller, connected to the linear controller, for receiving the pseudo control signal and for providing a modified pseudo control signal to correct for the errors made in modeling the nonlinearities in the process. A response network is also included as part of the computer system. The response network receives the modified pseudo control signal and provides the output response signal to the controlled device. The second controller preferably is a neural network. The computer system may include a plurality of neural networks with each neural network designated to control a selected variable or degree of freedom within the system.
摘要翻译：一种过程和神经网络架构，用于以校正由基于控制的过程的动力学的模型设计的非线性控制器所做的错误的方式在线调整神经网络的权重。提供了一种用于控制非线性物理过程的动态输出响应信号的计算机系统，其中物理过程由该过程的固定模型表示。计算机系统包括用于响应系统的输出响应信号的受控设备。计算机系统还包括线性控制器，用于提供基于该过程的固定模型的伪控制信号，并提供连接到线性控制器的第二控制器，用于接收伪控制信号并提供经修改的伪控制信号以纠正在过程中对非线性建模的错误。响应网络也作为计算机系统的一部分。响应网络接收修改后的伪控制信号，并向受控设备提供输出响应信号。第二控制器优选地是神经网络。计算机系统可以包括多个神经网络，每个神经网络被指定用于控制系统内的选定变量或自由度。

4. 发明授权

US07177710B2 System and method for adaptive control of uncertain nonlinear processes 有权
标题翻译：不确定非线性过程的自适应控制系统和方法
公开(公告)号：US07177710B2
公开(公告)日：2007-02-13
申请号：US11147671
申请日：2005-06-07
申请人： Anthony J. Calise , Byoung-Soo Kim
发明人： Anthony J. Calise , Byoung-Soo Kim
IPC分类号： G05B13/02 , G01C23/00 , G05D3/00 , G05D1/00 , G06F7/00 , G06F17/00 , G06F19/00
CPC分类号： G05B13/027 , G05D1/0825
摘要： A computer system for controlling a nonlinear physical process. The computer system comprises a linear controller and a neural network. The linear controller receives a command signal for control of the nonlinear physical process and a measured output signal from the output of the nonlinear physical process. The linear controller generates a control signal based on the command signal, a measured output signal, and a fixed linear model for the process. The neural network receives the control signal from the linear controller and the measured output signal from the output of the nonlinear physical process. The neural network uses the measured output signal to modify the connection weights of the neural network. The neural network also generates a modified control signal supplied to the linear controller to iterate a fixed point solution for the modified control signal used to control the nonlinear physical process.
摘要翻译：一种用于控制非线性物理过程的计算机系统。计算机系统包括线性控制器和神经网络。线性控制器接收用于控制非线性物理过程的命令信号和来自非线性物理过程的输出的测量输出信号。线性控制器基于命令信号，测量输出信号和用于该过程的固定线性模型产生控制信号。神经网络接收来自线性控制器的控制信号和来自非线性物理过程的输出的测量输出信号。神经网络使用测量的输出信号来修改神经网络的连接权重。神经网络还生成提供给线性控制器的修改的控制信号，以迭代用于控制非线性物理过程的修改的控制信号的固定点解。

5. 发明授权

US09494941B2 Method of guidance of unmanned aerial vehicles 有权
标题翻译：无人驾驶飞行器指导方法
公开(公告)号：US09494941B2
公开(公告)日：2016-11-15
申请号：US12824888
申请日：2010-06-28
申请人： Anthony J. Calise
发明人： Anthony J. Calise
IPC分类号： G01C22/00 , G05D1/00 , G05D1/02
CPC分类号： G05D1/0204
摘要： A method of guiding aerial vehicles to a target site in adverse weather conditions wherein the method regulates the range indirectly by regulating heading error to an offset target that revolves around the true target site. The improved guidance architecture is effective in adverse weather conditions, such as high winds.
摘要翻译：一种在恶劣天气条件下将飞行器引导到目标地点的方法，其中所述方法通过将朝向误差调整到围绕真实目标位置旋转的偏移目标而间接地调节范围。改进的指导架构在恶劣的天气条件下（如大风）是有效的。

6. 发明申请

US20090128408A1 System and Method For Maintaining Antenna Pointing Accuracy During Periods of GPS Outage 审中-公开
标题翻译： GPS停电期间维护天线指向精度的系统及方法
公开(公告)号：US20090128408A1
公开(公告)日：2009-05-21
申请号：US12175106
申请日：2008-07-17
申请人： Daniel J. Preston , Anthony J. Calise
发明人： Daniel J. Preston , Anthony J. Calise
IPC分类号： G01S5/14 , H01Q3/00
CPC分类号： G01S3/56 , G01S19/26 , H01Q1/125 , H01Q1/1257
摘要： A method of computing an antenna pointing direction for an inertial navigation unit (INU) utilizing a global positioning system (GPS) signal during periods of GPS signal outage includes determining antenna pointing error of magnitude and phase information. The phase information is obtained by detecting the angle where a signal to noise ratio of the antenna passes through a minimum level, and wherein the magnitude information is obtained by calculating the difference between the maximum and minimum signal to noise ratio of the antenna measured over one conical cycle of rotation of the antenna about an axis that is not parallel to a vector pointing from an antenna center to a GPS signal transmitting satellite. During periods of GPS signal outage, the determined magnitude and phase information is used to cause a nominal antenna beam axis to move by an amount that depends on the determined magnitude information in a direction defined by the determined phase information.
摘要翻译：在GPS信号中断周期期间利用全球定位系统（GPS）信号计算惯性导航单元（INU）的天线指向方向的方法包括确定幅度和相位信息的天线指向误差。通过检测天线的信噪比通过最小电平的角度来获得相位信息，并且其中通过计算在一个天线上测量的天线的最大和最小信噪比之间的差异来获得幅度信息围绕不平行于从天线中心到GPS信号发射卫星的矢量的轴的天线旋转的圆锥旋转。在GPS信号中断期间，确定的幅度和相位信息用于使标称天线波束轴移动一定量，该量取决于由所确定的相位信息确定的方向上所确定的幅度信息。

7. 发明授权

US07218973B2 Adaptive control system having hedge unit and related apparatus and methods 有权
标题翻译：具有对冲单元和相关设备和方法的自适应控制系统
公开(公告)号：US07218973B2
公开(公告)日：2007-05-15
申请号：US10602458
申请日：2003-06-23
申请人： Eric Norman Johnson , Anthony J. Calise
发明人： Eric Norman Johnson , Anthony J. Calise
IPC分类号： G05B13/02 , G06F7/00
CPC分类号： G05B13/04 , G05B13/027 , G05B13/041
摘要： The invention includes an adaptive control system used to control a plant. The adaptive control system includes a hedge unit that receives at least one control signal and a plant state signal. The hedge unit generates a hedge signal based on the control signal, the plant state signal, and a hedge model including a first model having one or more characteristics to which the adaptive control system is not to adapt, and a second model not having the characteristic(s) to which the adaptive control system is not to adapt. The hedge signal is used in the adaptive control system to remove the effect of the characteristic from a signal supplied to an adaptation law unit of the adaptive control system so that the adaptive control system does not adapt to the characteristic in controlling the plant.
摘要翻译：本发明包括用于控制设备的自适应控制系统。自适应控制系统包括接收至少一个控制信号和工厂状态信号的对冲单元。对冲单元基于控制信号，工厂状态信号和包括具有自适应控制系统不适应的一个或多个特性的第一模型的对冲模型产生套期信号，以及不具有特性的第二模型（s），自适应控制系统不适应。在自适应控制系统中使用对冲信号来消除从提供给自适应控制系统的适应定律单元的信号中的特性的影响，使得自适应控制系统不适应控制设备的特性。

8. 发明授权

US07418432B2 Adaptive control system having direct output feedback and related apparatuses and methods 有权
标题翻译：具有直接输出反馈的自适应控制系统及相关装置和方法
公开(公告)号：US07418432B2
公开(公告)日：2008-08-26
申请号：US11105826
申请日：2005-04-12
申请人： Anthony J. Calise , Naira Hovakimyan , Moshe Idan
发明人： Anthony J. Calise , Naira Hovakimyan , Moshe Idan
IPC分类号： G05B13/02 , G06E1/00 , G06E3/00 , G06F15/18 , G06G7/00
CPC分类号： G05B13/027
摘要： An adaptive control system (ACS) uses direct output feedback to control a plant. The ACS uses direct adaptive output feedback control developed for highly uncertain nonlinear systems, that does not rely on state estimation. The approach is also applicable to systems of unknown, but bounded dimension, whose output has known, but otherwise arbitrary relative degree. This includes systems with both parameter uncertainty and unmodeled dynamics. The result is achieved by extending the universal function approximation property of linearly parameterized neural networks to model unknown system dynamics from input/output data. The network weight adaptation rule is derived from Lyapunov stability analysis, and guarantees that the adapted weight errors and the tracking error are bounded.
摘要翻译：自适应控制系统（ACS）使用直接输出反馈来控制设备。 ACS使用针对高度不确定的非线性系统开发的直接自适应输出反馈控制，不依赖于状态估计。该方法也适用于未知但有界尺寸的系统，其输出已知，但以任意相对度计。这包括具有参数不确定性和未建模动力学的系统。结果是通过将线性参数化神经网络的通用函数近似属性扩展到来自输入/输出数据的未知系统动力学来实现。网络权重适应规则是从李亚普诺夫稳定性分析中得出的，并保证适应的权重误差和跟踪误差是有界的。

9. 发明授权

US06904422B2 Adaptive control system having direct output feedback and related apparatuses and methods 有权
公开(公告)号：US06904422B2
公开(公告)日：2005-06-07
申请号：US09865659
申请日：2001-05-25
申请人： Anthony J. Calise , Naira Hovakimyan , Moshe Idan
发明人： Anthony J. Calise , Naira Hovakimyan , Moshe Idan
IPC分类号： G05B13/02 , G06F15/18
CPC分类号： G05B13/027
摘要： An adaptive control system (ACS) uses direct output feedback to control a plant. The ACS uses direct adaptive output feedback control developed for highly uncertain nonlinear systems, that does not rely on state estimation. The approach is also applicable to systems of unknown, but bounded dimension, whose output has known, but otherwise arbitrary relative degree. This includes systems with both parameter uncertainty and unmodeled dynamics. The result is achieved by extending the universal function approximation property of linearly parameterized neural networks to model unknown system dynamics from input/output data. The network weight adaptation rule is derived from Lyapunov stability analysis, and guarantees that the adapted weight errors and the tracking error are bounded.

10. 发明授权

US06611823B1 Backlash compensation using neural network 失效
标题翻译：使用神经网络的间隙补偿
公开(公告)号：US06611823B1
公开(公告)日：2003-08-26
申请号：US09553601
申请日：2000-04-20
申请人： Rastko R. Selmic , Frank L. Lewis , Anthony J. Calise , Michael B. McFarland
发明人： Rastko R. Selmic , Frank L. Lewis , Anthony J. Calise , Michael B. McFarland
IPC分类号： G06F1518
CPC分类号： G05B13/027
摘要： Methods and systems for backlash compensation. Restrictive assumptions on the backlash nonlinearity (e.g. the same slopes of the lines, etc.) are not required. The compensator scheme has dynamic inversion structure, with a neural network in the feedforward path that approximates the backlash inversion error plus filter dynamics needed for backstepping design. The neural network controller does not require preliminary off-line training. Neural network tuning is based on a modified Hebbian tuning law, which requires less computation than backpropagation. The backstepping controller uses a practical filtered derivative, unlike the usual differentiation required by earlier backstepping routines. Rigorous stability proofs are given using Lyapunov theory. Simulation results show that the proposed compensation scheme is an efficient way of improving the tracking performance of a vast array of nonlinear systems with backlash.
摘要翻译：反向补偿的方法和系统不需要对间隙非线性的限制性假设（例如线的相同斜率等）。补偿方案具有动态反演结构，前馈路径中的神经网络近似反向反转误差加上后台设计所需的滤波器动力学。神经网络控制器不需要初步的离线训练。神经网络调谐是基于修正的Hebbian调整定律，与反向传播相比，需要的计算量较少。后台控制器使用实际的过滤导数，与早期后台程序所需的通常差异不同。使用李亚普诺夫理论给出了严格的稳定性证明。仿真结果表明，提出的补偿方案是改善具有反向间隙的大量非线性系统的跟踪性能的有效方法。

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