Towards a fixed point QP solver for predictive control
Towards a fixed point QP solver for predictive control
复制标题
用于预测控制的定点 QP 求解器
DOI：
10.1109/cdc.2012.6427015
复制
发表时间：
2012
期刊：
影响因子：
--
通讯作者：
E. Kerrigan
中科院分区：
文献类型：
--
作者：
J. Jerez;G. Constantinides;E. Kerrigan
需要用于凸二次规划的高速、低成本和低能量解决方案，以使得模型预测控制（MPC）能够在比当前可能的更广泛的应用集合中实现。对于大多数二次规划（QP）求解器的计算瓶颈是线性方程组的解决方案，我们建议使用迭代线性求解器的固定点实现来解决，以允许在并行硬件中进行快速有效的计算。然而，定点算法提出了额外的挑战，例如必须限制变量的峰值并限制其动态范围。对于这些类型的算法，问题不能通过当前的工具自动化。我们采用了一种新的方式，使我们能够建立严格的分析边界上的所有变量的Lanczos过程，现代迭代线性求解算法的心脏。所提出的方法进行评估，通过实施一个混合精度的走廊点控制器的波音747飞机。数值结果表明，从浮点到定点的移动并不一定会损失控制质量。
There is a need for high speed, low cost and low energy solutions for convex quadratic programming to enable model predictive control (MPC) to be implemented in a wider set of applications than is currently possible. For most quadratic programming (QP) solvers the computational bottleneck is the solution of systems of linear equations, which we propose to solve using a fixed-point implementation of an iterative linear solver to allow for fast and efficient computation in parallel hardware. However, fixed point arithmetic presents additional challenges, such as having to bound peak values of variables and constrain their dynamic ranges. For these types of algorithms the problems cannot be automated by current tools. We employ a preconditioner in a novel manner to allow us to establish tight analytical bounds on all the variables of the Lanczos process, the heart of modern iterative linear solving algorithms. The proposed approach is evaluated through the implementation of a mixed precision interior-point controller for a Boeing 747 aircraft. The numerical results show that there does not have to be a loss of control quality by moving from floating-point to fixed-point.
使用 FPGA 对波音 747 飞机进行预测控制
DOI：
10.3182/20120823-5-nl-3013.00016
发表时间：
2012
期刊：
IFAC Proceedings Volumes
影响因子：
--
作者：
Hartley E
通讯作者：
Hartley E
基于 FPGA 的科学计算的数值数据表示
影响因子：
--
作者：
Constantinides G
通讯作者：
Constantinides G