Predictive control using an FPGA with application to aircraft control

Alternative and more efficient computational methods can extend the applicability of 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) 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-inthe-loop testbench controlling a nonlinear simulation of a large airliner. This study considers many more manipulated inputs than any previous FPGA-based MPC implementation to date, yet the implementation comfortably fits into a mid-range 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

A low complexity scaling method for the Lanczos Kernel in fixed-point arithmetic

We consider the problem of enabling fixed-point implementation of linear algebra kernels on low-cost embedded systems, as well as motivating more efficient computational architectures for scientific applications. Fixed-point arithmetic presents additional design challenges compared to floating-point arithmetic, such as having to bound peak values of variables and control their dynamic ranges. Algorithms for solving linear equations or finding eigenvalues are typically nonlinear and iterative, making solving these design challenges a nontrivial task. For these types of algorithms, the bounding problem cannot be automated by current tools. We focus on the Lanczos iteration, the heart of well-known methods such as conjugate gradient and minimum residual. We show how one can modify the algorithm with a low-complexity scaling procedure to allow us to apply standard linear algebra to derive tight analytical bounds on all variables of the process, regardless of the properties of the original matrix. It is shown that the numerical behavior of fixed-point implementations of the modified problem can be chosen to be at least as good as a floating-point implementation, if necessary. The approach is evaluated on field-programmable gate array (FPGA) platforms, highlighting orders of magnitude potential performance and efficiency improvements by moving form floating-point to fixed-point computation

Predictive control of a Boeing 747 aircraft using an FPGA

New embedded predictive control applications call for more efficient ways of solving quadratic programs (QPs) in order to meet demanding real-time, power and cost requirements. A single precision QP-on-a-chip controller is proposed, implemented in a field-programmable gate array (FPGA) with an iterative linear solver at its core. A novel offline scaling procedure is introduced to aid the convergence of the reduced precision solver. The feasibility of the proposed approach is demonstrated with a real-time hardware-in-the-loop (HIL) experimental setup where an ML605 FPGA board controls a nonlinear model of a Boeing 747 aircraft running on a desktop PC through an Ethernet link. Simulations show that the quality of the closed-loop control and accuracy of individual solutions is competitive with a conventional double precision controller solving linear systems using a Riccati recursion.This work was supported by the EPSRC (Grants EP/G031576/1, EP/G030308/1 and EP/I012036/1) and the EU FP7 Project EMBOCON, as well as industrial support from Xilinx, the Mathworks, and the European Space Agency.IFAC Conference on Nonlinear Model Predictive Control 2012 (NMPC'12), Noordwijkerhout, the Netherlands on August 23 - 27, 2012

Predictive control using an FPGA with application to aircraft control

Alternative and more efficient computational methods can extend the applicability of 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) 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 study considers many more manipulated inputs than any previous FPGA-based MPC implementation to date, yet the implementation comfortably fits into a mid-range 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.This work was supported by EPSRC (Grants EP/G030308/1, EP/G031576/1 and EP/I012036/1) and the EU FP7 Project EMBOCON grant agreement number FP7-ICT-2009-4 248940, as well as industrial support from Xilinx, the Mathworks, and the European Space Agency.This is the author's version of an article that has been published in this journal. Changes were made to this version by the publisher prior to publication. The final version of record is available at: http://dx.doi.org/10.1109/TCST.2013.2271791. Copyright (c) 2014 IEEE. Personal use is permitted. For any other purposes, permission must be obtained from the IEEE by emailing [email protected]

Exploiting Chordality in Optimization Algorithms for Model Predictive Control

In this chapter we show that chordal structure can be used to devise efficient optimization methods for many common model predictive control problems. The chordal structure is used both for computing search directions efficiently as well as for distributing all the other computations in an interior-point method for solving the problem. The chordal structure can stem both from the sequential nature of the problem as well as from distributed formulations of the problem related to scenario trees or other formulations. The framework enables efficient parallel computations.Comment: arXiv admin note: text overlap with arXiv:1502.0638

Metabolic responses to high pCO2 conditions at a CO2 vent site in juveniles of a marine isopod species assemblage

We are starting to understand the relationship between metabolic rate responses and species' ability to respond to exposure to high pCO2. However, most of our knowledge has come from investigations of single species. The examination of metabolic responses of closely related species with differing distributions around natural elevated CO2 areas may be useful to inform our understanding of their adaptive significance. Furthermore, little is known about the physiological responses of marine invertebrate juveniles to high pCO2, despite the fact they are known to be sensitive to other stressors, often acting as bottlenecks for future species success. We conducted an in situ transplant experiment using juveniles of isopods found living inside and around a high pCO2 vent (Ischia, Italy): the CO2 'tolerant' Dynamene bifida and 'sensitive' Cymodoce truncata and Dynamene torelliae. This allowed us to test for any generality of the hypothesis that pCO2 sensitive marine invertebrates may be those that experience trade-offs between energy metabolism and cellular homoeostasis under high pCO2 conditions. Both sensitive species were able to maintain their energy metabolism under high pCO2 conditions, but in C. truncata this may occur at the expense of [carbonic anhydrase], confirming our hypothesis. By comparison, the tolerant D. bifida appeared metabolically well adapted to high pCO2, being able to upregulate ATP production without recourse to anaerobiosis. These isopods are important keystone species; however, given they differ in their metabolic responses to future pCO2, shifts in the structure of the marine ecosystems they inhabit may be expected under future ocean acidification conditions

Methotrexate Is a JAK/STAT Pathway Inhibitor

Background: The JAK/STAT pathway transduces signals from multiple cytokines and controls haematopoiesis, immunity and inflammation. In addition, pathological activation is seen in multiple malignancies including the myeloproliferative neoplasms (MPNs). Given this, drug development efforts have targeted the pathway with JAK inhibitors such as ruxolitinib. Although effective, high costs and side effects have limited its adoption. Thus, a need for effective low cost treatments remains. Methods & Findings: We used the low-complexity Drosophila melanogaster pathway to screen for small molecules that modulate JAK/STAT signalling. This screen identified methotrexate and the closely related aminopterin as potent suppressors of STAT activation. We show that methotrexate suppresses human JAK/STAT signalling without affecting other phosphorylation-dependent pathways. Furthermore, methotrexate significantly reduces STAT5 phosphorylation in cells expressing JAK2 V617F, a mutation associated with most human MPNs. Methotrexate acts independently of dihydrofolate reductase (DHFR) and is comparable to the JAK1/2 inhibitor ruxolitinib. However, cells treated with methotrexate still retain their ability to respond to physiological levels of the ligand erythropoietin. Conclusions: Aminopterin and methotrexate represent the first chemotherapy agents developed and act as competitive inhibitors of DHFR. Methotrexate is also widely used at low doses to treat inflammatory and immune-mediated conditions including rheumatoid arthritis. In this low-dose regime, folate supplements are given to mitigate side effects by bypassing the biochemical requirement for DHFR. Although independent of DHFR, the mechanism-of-action underlying the low-dose effects of methotrexate is unknown. Given that multiple pro-inflammatory cytokines signal through the pathway, we suggest that suppression of the JAK/STAT pathway is likely to be the principal anti-inflammatory and immunosuppressive mechanism-of-action of low-dose methotrexate. In addition, we suggest that patients with JAK/STAT-associated haematological malignancies may benefit from low-dose methotrexate treatments. While the JAK1/2 inhibitor ruxolitinib is effective, a £43,200 annual cost precludes widespread adoption. With an annual methotrexate cost of around £32, our findings represent an important development with significant future potential