Sensitivity-based multistep MPC for embedded systems

In model predictive control (MPC), an optimization problem is solved every sampling instant to determine an optimal control for a physical system. We aim to accelerate this procedure for fast systems applications and address the challenge of implementing the resulting MPC scheme on an embedded system with limited computing power. We present the sensitivity-based multistep MPC, a strategy which considerably reduces the computing requirements in terms of floating point operations (FLOPs), compared to a standard MPC formulation, while fulfilling closed- loop performance expectations. We illustrate by applying the method to a DC-DC converter model and show how a designer can optimally trade off closed-loop performance considerations with computing requirements in order to fit the controller into a resource-constrained embedded system

Computer Architectures to Close the Loop in Real-time Optimization

© 2015 IEEE.Many modern control, automation, signal processing and machine learning applications rely on solving a sequence of optimization problems, which are updated with measurements of a real system that evolves in time. The solutions of each of these optimization problems are then used to make decisions, which may be followed by changing some parameters of the physical system, thereby resulting in a feedback loop between the computing and the physical system. Real-time optimization is not the same as fast optimization, due to the fact that the computation is affected by an uncertain system that evolves in time. The suitability of a design should therefore not be judged from the optimality of a single optimization problem, but based on the evolution of the entire cyber-physical system. The algorithms and hardware used for solving a single optimization problem in the office might therefore be far from ideal when solving a sequence of real-time optimization problems. Instead of there being a single, optimal design, one has to trade-off a number of objectives, including performance, robustness, energy usage, size and cost. We therefore provide here a tutorial introduction to some of the questions and implementation issues that arise in real-time optimization applications. We will concentrate on some of the decisions that have to be made when designing the computing architecture and algorithm and argue that the choice of one informs the other

Robust explicit MPC design under finite precision arithmetic

We propose a design methodology for explicit Model Predictive Control (MPC) that guarantees hard constraint satisfaction in the presence of finite precision arithmetic errors. The implementation of complex digital control techniques, like MPC, is becoming increasingly adopted in embedded systems, where reduced precision computation techniques are embraced to achieve fast execution and low power consumption. However, in a low precision implementation, constraint satisfaction is not guaranteed if infinite precision is assumed during the algorithm design. To enforce constraint satisfaction under numerical errors, we use forward error analysis to compute an error bound on the output of the embedded controller. We treat this error as a state disturbance and use this to inform the design of a constraint-tightening robust controller. Benchmarks with a classical control problem, namely an inverted pendulum, show how it is possible to guarantee, by design, constraint satisfaction for embedded systems featuring low precision, fixed-point computations

Energy-aware MPC co-design for DC-DC converters

In this paper, we propose an integrated controller design methodology for the implementation of an energy-aware explicit model predictive control (MPC) algorithms, illustrat- ing the method on a DC-DC converter model. The power consumption of control algorithms is becoming increasingly important for low-power embedded systems, especially where complex digital control techniques, like MPC, are used. For DC-DC converters, digital control provides better regulation, but also higher energy consumption compared to standard analog methods. To overcome the limitation in energy efficiency, instead of addressing the problem by implementing sub-optimal MPC schemes, the closed-loop performance and the control algorithm power consumption are minimized in a joint cost function, allowing us to keep the controller power efficiency closer to an analog approach while maintaining closed-loop op- timality. A case study for an implementation in reconfigurable hardware shows how a designer can optimally trade closed-loop performance with hardware implementation performance

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

Kkn-ppm Sebagai Akselerator Pemanfaatan Potensi Sumberdaya Alam Desa

Desa dikenal sebagai sebuah komunitas yang diatur dalam lingkup administratif kewilayahan. Desa terkebelakang dan tertinggal diakibatkan oleh wilayah yang terpencil dan terisolir, kebanyakan berada pada dataran tinggi atau pegunungan. Kategori ini merupakan kategori Desa Salo Dua, Kecamatan Maiwa, Kabupaten Enrekang yang menjadi lokasi pelaksanaan KKN-PPM Universitas Islam Makassar. Persamalah-permaslahan yang dihadapi masyarakat Desa Salo Dua antara lain lahan sawah didominasi oleh lahan tadah hujan sehingga produksi tanaman pangan utamanya padi belum optimal, terdapat lahan terlantar yang cukup luas utamanya yang tidak termanfaatkan oleh warga masyarakat, pemeliharaan ternak yang masih tradisional, limbah ternak dan limbah peranian belum dimanfaatkan untuk memproduksi produk-produk ekonomis seperti pupuk organik dan biogas serta pembuatan gula merah dilakukan dengan teknologi manual sederhana. Tujuan KKN-PPM ini adalah meningkatkan kapasitas masyarakat dalam memanfaatkan sumberdaya alam untuk meningkatkan kesejahteraannya. Kegiatan-kegiatan mahasiswa KKN-PPM yang dilaksanakan antara lain peningkatan produksi, efisiensi, peningkatan partisipasi, perbaikan system dan peningkatan swadana dan swadaya masyarakat. Kegiatan tersebut dilakukan dengan motode pelatihan in-situ maupun sekolah lapang, seperti peningkatan produksi dengan pemanfaatan lahan kering, introduksi teknologi pengolahan gula aren, introduksi teknologi inseminasi buatan terhadap ternak sapi, pembuatan instalasi biogas

Perbandingan Performans Reproduksi Kuda Lokal dan Turunan Thoroughbred di Kota Payakumbuh

This study aimed to compare the performance of reproduction between local horses and descendant of Thoroughbred in Payakumbuh. In this study used a sample of 60 mares productive which have a complete recording. This research was a field research with survey method. Samples were taken by purposive sampling technique. The parameters were observed in between the age of first marriage, old pregnant, and lust after lambing. The results showed that the average age of first marriage in the Local horse was 26.2 ± 8.53 months while on horseback Throughbred derivative obtained at 51.8 ± 14.5 months, the average of pregnant time of Local horse was 323.17 ± 8.55 days while on horseback derivative Throughbred amounted to 324.37 ± 14 185 days and the median lust after lambing on Local horse was at 16.37 ± 9.37 days while on horseback Throughbred derivative obtained at 10.9 ± 6.64 days

Social and Financial Performance of Rural Microfinance Instution Ued-sp Bakti Mulya Talang Mulya Village Batang Cenaku Subdistrict Indragirihulu Regency

This study aims to analyze social and financial performance of microfinance institutions UED-SP Bakti Mulya. Social performance analyzed using Microfinance Information exchange (MIX) soscial performance standard report, and financial performance analyzed using 17 PEARLS ratio. Analysis of the UED-SP social peformance has reached the social mission and goals the cumulative volume of loans 19.42 percent, and the higher growth of loans volume is the agricultural sector 39.18 percent. The poor borrowers 23.33 percent and volume of loans increased 35.06 percent. Internal systems increased on a variety of loan products and increased incentives for staff. The output and outcome UED-SP was increasing in average annual, outreach of the women borrowers, the borrower of productive economic in the agricultural sector, poor borrowers, and the volume of saving. Monetary performance LKM UED-SP Talang Mulya show from 17 indicator ratio of PEARLS there are 8 indicator residing in condition is not ideal cover protection ratio ( protection) ( P1), and ( P2), lending ratio circulate ( E1), Share deposit ratio ( E7) and operating expenses ratio (R9),Rasio not yield ( L3), growth of share deposit ( S5), and growth of institute capital (S6) show condition is not ideal. Implication Policy of Social Performance that is organizer require to follow training related to gender sensitivitas, Need the existence of development of product innovation, accepted incentive staff have to pursuant to performance. Implication policy of monetary performance have to cast aside risk reserve fund to avoid arrears risk