An embedded hardware architecture for GPC-on-Chip applied to automotive active suspension systems

This paper presents a hardware architecture for an embedded real-time generalized predictive control (GPC) algorithm based on the state-of-the-art Customizable Advanced Processor (CAP9) technology from Atmel; targeting automotive active suspension systems. The GPC algorithm relies on the solution of an optimization problem at every sampling period. Profiling shows that matrix operations consume the largest portion of the computation requirements of the algorithm. The proposed embedded system utilizes a systolic-array based matrix co-processor in order to accelerate matrix operations. The proposed embedded system is designed to fit within the proposed platform while meeting tight real-time constraints imposed by the automotive active suspension systems.

本文提出了一种基于爱特梅尔公司最先进的可定制高级处理器（CAP9）技术的嵌入式实时广义预测控制（GPC）算法的硬件架构，其目标应用是汽车主动悬架系统。GPC算法在每个采样周期都依赖于一个优化问题的求解。性能分析表明，矩阵运算占据了该算法计算需求的最大部分。所提出的嵌入式系统利用了一个基于脉动阵列的矩阵协处理器来加速矩阵运算。所设计的嵌入式系统旨在适应所提出的平台，同时满足汽车主动悬架系统所施加的严格实时约束。