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System and method for exploiting a good starting guess for binding constraints in quadratic programming with an infeasible and inconsistent starting guess for the solution
System and method for exploiting a good starting guess for binding constraints in quadratic programming with an infeasible and inconsistent starting guess for the solution
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机译:利用二次编程中的约束约束的良好的开始猜测以及该解决方案的不可行和不一致的开始猜测的系统和方法
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摘要
The present invention provides A method for controlling a multivariable system including the steps of: a) receiving a plurality of sensor signals indicating current conditions of the system; b) receiving a plurality of commands; c) determining the desired dynamic response of the system based upon the commands and the sensor signals; d) in each of a plurality of time steps, formulating a problem of controlling the system to achieve the desired dynamic response as a solution to a quadratic programming problem; e) solving the quadratic programming problem in each time step using an iterative algorithm which searches for an optimal active set, wherein the active set comprises a set of constraints that are binding at an optimized solution; and f) in each subsequent time step of the plurality of time steps: g) solving the quadratic programming problem based on a final active set of a prior time step of the plurality of time steps to obtain xf; h) initializing a search for the optimal active set based on the final active set of the prior time step of the plurality of time steps and based upon the assumption that xf is feasible.
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机译:本发明提供了一种用于控制多变量系统的方法,该方法包括以下步骤:a)接收指示系统当前状况的多个传感器信号;以及b)接收多个命令; c)基于命令和传感器信号确定系统的期望动态响应; d)在多个时间步长的每一个中,提出一个控制系统以实现期望的动态响应的问题,作为对二次规划问题的解决方案; e)在每个时间步中使用迭代算法来求解二次规划问题,该迭代算法搜索最佳活动集,其中活动集包括约束条件的集合,这些约束条件以最优解进行绑定; f)在多个时间步中的每个后续时间步中:g)基于多个时间步中的先前时间步的最终活动集求解二次规划问题,以获得x f Sub> ; h)基于多个时间步中先前时间步的最终活动集并基于x f Sub>可行的假设,初始化对最佳活动集的搜索。
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