期刊
IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY
卷 22, 期 3, 页码 1006-1017出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TCST.2013.2271791
关键词
Aerospace control; field-programmable gate arrays (FPGAs); optimization methods; predictive control
资金
- EPSRC [EP/G030308/1, EP/G031576/1, EP/I012036/1]
- EU FP7 Project EMBOCON [FP7-ICT-2009-4 248940]
- Xilinx
- MathWorks
- European Space Agency
- Engineering and Physical Sciences Research Council [EP/I012036/1, EP/G030308/1, EP/C512596/1, EP/G031576/1] Funding Source: researchfish
- EPSRC [EP/I012036/1, EP/G031576/1, EP/G030308/1] Funding Source: UKRI
Alternative and more efficient computational methods can extend the applicability of model predictive control (MPC) to systems with tight real-time requirements. This paper presents a system-on-a-chip MPC system, implemented on a field-programmable gate array (FPGA), consisting of a sparse structure-exploiting primal dual interior point (PDIP) quadratic program (QP) solver for MPC reference tracking and a fast gradient QP solver for steady-state target calculation. A parallel reduced precision iterative solver is used to accelerate the solution of the set of linear equations forming the computational bottleneck of the PDIP algorithm. A numerical study of the effect of reducing the number of iterations highlights the effectiveness of the approach. The system is demonstrated with an FPGA-in-the-loop testbench controlling a nonlinear simulation of a large airliner. This paper considers many more manipulated inputs than any previous FPGA-based MPC implementation to date, yet the implementation comfortably fits into a midrange FPGA, and the controller compares well in terms of solution quality and latency to state-of-the-art QP solvers running on a standard PC.
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