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    • 2. 发明申请
    • Method for Solving Control Problems
    • 解决控制问题的方法
    • US20120150324A1
    • 2012-06-14
    • US12962744
    • 2010-12-08
    • Matthew BrandVijay ShilpiekandulaScott A. Bortoff
    • Matthew BrandVijay ShilpiekandulaScott A. Bortoff
    • G05B13/04
    • G05B13/048
    • A method solves a quadratic programming (QP) problem in real-time implementations of model predictive control for automation applications. The method can be implemented for fine-grained parallel solutions. Due to the extreme simplicity of the method, even serial implementations offer considerable speed advantages. The method solves the problem by formulating, over a predetermined time interval, an optimization problem with a quadratic cost function, and linear state and control constraints as a quadratic program for the application. Then, the quadratic program is solved by applying a parallel quadratic programming update law starting from a positive initial estimate to obtain control actions for the application.
    • 一种方法解决了自动化应用中模型预测控制的实时实现中的二次规划(QP)问题。 该方法可以实现细粒度并行解决方案。 由于该方法非常简单,即使串行实现也提供了相当快的优势。 该方法通过在预定的时间间隔内通过二次成本函数,线性状态和控制约束作为应用程序的二次方案来制定问题。 然后,通过应用从正初始估计开始的并行二次规划更新定律来求解二次程序,以获得应用的控制动作。
    • 4. 发明授权
    • Method for solving control problems
    • 解决控制问题的方法
    • US08554343B2
    • 2013-10-08
    • US12962744
    • 2010-12-08
    • Matthew BrandVijay ShilpiekandulaScott A Bortoff
    • Matthew BrandVijay ShilpiekandulaScott A Bortoff
    • G05B13/02
    • G05B13/048
    • A method solves a quadratic programming (QP) problem in real-time implementations of model predictive control for automation applications. The method can be implemented for fine-grained parallel solutions. Due to the extreme simplicity of the method, even serial implementations offer considerable speed advantages. The method solves the problem by formulating, over a predetermined time interval, an optimization problem with a quadratic cost function, and linear state and control constraints as a quadratic program for the application. Then, the quadratic program is solved by applying a parallel quadratic programming update law starting from a positive initial estimate to obtain control actions for the application.
    • 一种方法解决了自动化应用中模型预测控制的实时实现中的二次规划(QP)问题。 该方法可以实现细粒度并行解决方案。 由于该方法非常简单,即使串行实现也提供了相当快的优势。 该方法通过在预定的时间间隔内通过二次成本函数,线性状态和控制约束作为应用程序的二次方案来制定问题。 然后,通过应用从正初始估计开始的并行二次规划更新定律来求解二次程序,以获得应用的控制动作。