Performance-Improved Implementation of the SISO Adaptive Predictive Control Algorithm for Embedded Systems

This article presents a performance improvement over a previously published software-based embedded implementation of the single-input single-output (SISO) adaptive predictive control (APC) algorithm. This article mainly focuses on reducing the execution time of a control iteration of the SISO APC algorithm, while preserving precision. A profiling study of the algorithm is developed, which identifies the performance bottlenecks. Analyzing the outcomes of the profiling study, a set of enhancements for efficient computations of the Recursion and Adaptation stages of the SISO APC algorithm is proposed, which greatly reduces the computational complexity of the algorithm. The ZYBO development board is the selected platform for testing. Firmware development and optimization is oriented to provide speedup using hardware acceleration, exploiting the processor in the ZYBO at its full extents, targeting the available coprocessors embedded in the core. Comparison with previously published work shows outstanding improvements in execution time, obtaining speedup increments up to $\text{12.0}\times$. The enhancements performed to the SISO APC algorithm along with firmware optimization allow the proposed implementation to run at execution times as low as 0.7 $\mu$s, which are considerably lower than existing embedded MPC implementations found in the literature.