کنترل پیش بینی غیرمستقیم بر روی یک پلت فرم محاسباتی ناهمگن

Nonlinear Model Predictive Control (NMPC) is an advanced control technique that often relies on computationally demanding optimization and integration algorithms. This paper proposes and investigates a heterogeneous hardware implementation of an NMPC controller based on an interior point algorithm. The proposed implementation provides flexibility of splitting the workload between a general-purpose CPU with a fixed architecture and a field-programmable gate array (FPGA) to trade off contradicting design objectives, namely performance and computational resource usage. A new way of exploiting the structure of the Karush-Kuhn-Tucker (KKT) matrix yields significant memory savings, which is crucial for reconfigurable hardware. For the considered case study, a 10x memory savings compared to existing approaches and a 10x speedup over a software implementation are reported. The proposed implementation can be tested from Matlab using a new release of the Protoip software tool, which is another contribution of the paper. Protoip abstracts many low-level details of heterogeneous hardware programming and allows quick prototyping and processor-in-the-loop verification of heterogeneous hardware implementations.