Cara Kerja DIDO

Bayangkan Anda mendengar telepon berdering. Apa hal pertama yang Anda lakukan? Itu mungkin tergantung pada banyak hal, seperti di mana Anda berada, waktu, apa yang Anda lakukan, siapa yang bersama Anda, seperti apa nada deringnya dan apakah itu benar-benar ponsel Anda. Jika Anda sedang berjalan melalui toko kelontong dan Anda mendengar telepon berdering dari beberapa gang jauhnya, Anda mungkin akan menyadari bahwa itu bukan telepon Anda dan abaikan saja. Jika Anda berada di dalam mobil, Anda dapat memutuskan apakah Anda dapat menjawab telepon berdasarkan lalu lintas atau apakah Anda memiliki perangkat handsfree.

Itu banyak variabel hanya untuk memutuskan apakah akan menjawab telepon, dan Anda mungkin bisa memikirkan banyak alasan lain Anda mungkin menjawab atau mengabaikan telepon berdering. Otak kita adalah komputer yang kuat yang dapat dengan cepat memproses semua kondisi itu, memutuskan respons terbaik, dan memerintahkan tubuh kita untuk mengambil tindakan. Sepanjang sejarah manusia, menciptakan mesin yang dapat mereplikasi proses itu dengan benar di setiap skenario hampir tak terbayangkan. Namun, hari ini, teknologi seperti perangkat lunak dan perangkat keras DIDO membantu membuat mesin seperti itu menjadi kenyataan.

Sama seperti tidak ada satu jawaban yang benar untuk telepon berdering, tidak ada satu cara yang benar untuk mengemudikan pesawat atau menggerakkan kaki robot. Namun, mungkin ada respons terbaik, mengingat semua kondisi yang memengaruhi skenario. Dalam kasus pesawat, cara pilot mengarahkan ke tujuan dipengaruhi oleh ketinggian, kecepatan, arah angin, kecepatan udara, dan salah satu dari seratus variabel lainnya pada saat tertentu. Pilot manusia memproses dan menanggapi semua informasi ini.

Bisakah komputer benar-benar meniru proses ini? Di situlah teknologi seperti DIDO masuk. DIDO adalah perangkat lunak yang diprogram untuk berjalan pada platform komputasi ilmiah MATLAB yang, pada gilirannya, membutuhkan Microsoft Windows. Komputer dapat menggunakan DIDO untuk memproses data dalam jumlah besar dan selalu berubah menjadi respons terbaik yang andal. DIDO dikembangkan pada akhir 1990-an oleh profesor Sekolah Pascasarjana Angkatan Laut AS Isaac "Mike" Ross. Saat itu, Ross dan rekannya Fariba Fahroo sedang melakukan penelitian dalam teori kontrol dan komputasi optimal. Kita akan melihat lebih lanjut pada teori kontrol optimal nanti.

Today, DIDO is part of hardware and software solutions marketed by Elissar Global. This article covers the kinds of problems DIDO is helping to solve and some breathtaking technological applications of DIDO optimal control technology. Let's start with a look at how researchers across many fields are making use of DIDO.

1. Pseudospectral Optimal Control
2. DIDO in Space
3. Other DIDO Applications

The term for the problem DIDO is solving is optimal control. In calculus, optimal control theory is a mathematical approach to finding the best mechanical response in a given scenario given some set of conditions. Mathematically, optimal control is a set of differential equations that minimize the cost (maximize the payoff) of achieving some desired outcome. Don't worry! We're about to make this concept much simpler.

To understand optimal control, let's freeze time for a moment. Take in the sensations of the world around you: sights, sounds, smells, tastes and physical feelings. Now combine that with everything stored in your brain . The way you respond to any new stimulus around you will be based on all that information. How would you react right now to hearing a doorbell or to smelling freshly baked cookies?

Computers can convert similar sensory information into data in an attempt to imitate our brainpower. The computer can calculate the best response to a given stimulus using all that data. From the computer's perspective, the "best" response would be the action that has the maximum payoff at the minimum cost. That best response concept is what scientists and mathematicians refer to as the optimal control.

Now let's unfreeze time and move forward again. Suddenly, calculating the optimal control is more complicated. As each fraction of a second passes, conditions change, with new sensory data to consider. Thus, the biggest challenge for finding the optimal control is considering these ever-changing conditions and recalculating accordingly. Our brains make these recalculations constantly, but a computer has to have some type of stimulus-response program to do this.

This compounded optimal control problem requires adding another calculus concept: pseudospectral theory. Pseudospectral theory involves using approximate values for optimal control calculations, within some known constraints. DIDO software is known for its pseudospectral approach to optimal control problems. Thus, DIDO helps drive machines that need to constantly re-evaluate their surrounding conditions and respond accordingly, including cars and airplanes.

So far we've determined what optimal control is and the significance of pseudospectral theory. Next, let's zoom in, or rather out, to outer space , where DIDO's had its most prominent application.

Dido's Problem

Ancient Roman and Greek history includes a woman named Elissar, or Elissa, known as the Queen of Carthage. She was also called Dido, particularly in Virgil's "Aeneid." Legend has it that Dido fled her native Phoenicia with several others, and when she found a place she wanted to settle, she struck a deal with the king there to obtain the land that would become the city of Carthage (in modern-day Tunisia). In the deal, Dido would get the amount of land she could mark out with a bull's hide. Dido and her colleagues made a long string from small strips cut from a single bull's hide. Then, they selected the coastline as a boundary and laid the string into a semi-circle with that coastal border. The king was surprised that the newcomers were able to mark such a large amount of land. In mathematics, Dido's Problem is the name given to finding the figure that produces the maximum area given a boundary line and a perimeter for the remaining sides. The figure that produces that maximum area is, as the legendary Dido observed, a semi-circle along that given boundary line.

According to Elissar Global, the most extensive application of its software has been in space. This is probably the most intuitive application for DIDO being that vehicles and other machines in space rely heavily on automation or remote controls rather than direct human actions. Out there, a computer that can sense what's happening around it and quickly determine the best response is a valuable asset.

Two particular applications of DIDO have given software's reputation for solving optimal control problems quite a boost. The first of these was in 2006, when DIDO tackled the goal of maneuvering the International Space Station (ISS) 180 degrees within its orbital path without expending any fuel. Typically, the ISS and other vehicles in orbit must use thrusters to maneuver, which require expensive fuel. DIDO creator Ross and other researchers had an idea that a zero-propellant maneuver (ZPM) was possible.

DIDO was used twice for these zero-propellant maneuvers, each with success. On Nov. 5, 2006, the team maneuvered the ISS 90 degrees. Four months later, on March 3, they managed a 180-degree turn. These experiments were a large-scale proof of concept for DIDO, launching it into fame as the leading optimal control technology.

In 2010, another application of DIDO was to maneuver NASA 's Transition Region and Coronal Explorer (TRACE) satellite. TRACE was on a mission to study the sun, but it had barely moved during its 12-year undertaking. As the TRACE research showed, NASA's protocol of following a straight line between two points may have identified the shortest distance to travel, but it was far from the fastest route. So, when the satellite needed to slew (move at an angle) to a new point, it was taking much longer than necessary, because it was trying to stick to that straight path.

The TRACE maneuvering research came just as the satellite was about to be decommissioned by the NASA Engineering and Safety Center (NESC). Engineers from NESC let Mark Karpenko take the lead in an experiment to apply DIDO calculations and uplink an optimal slew for the TRACE. The hypothesis was that the optimum path using gravity as an advantage would make for a more efficient approach to slewing. This idea relates to Bernoulli's principle in physics.

Despite its limited two-month turn around, the TRACE research team was able to prove its hypothesis. In addition, the TRACE required less than half the electrical power during each slew. Observers described the TRACE satellite maneuver as if it were dancing through space. Now that's what we call dancing with the stars!

Selanjutnya, kita keluar dari orbit dan melihat bagaimana DIDO menjadi besar di Bumi.

DIDO dimaksudkan sebagai pendekatan umum untuk memecahkan masalah kontrol yang optimal. Ini berarti bahwa ia harus siap berintegrasi ke dalam sistem otonom apa pun jenis input apa yang sedang diproses sistem, selama ia menggunakan platform komputasi MATLAB yang berjalan di Microsoft Windows. Dengan sistem otonom, yang kami maksud adalah kombinasi perangkat keras dan perangkat lunak yang berfungsi bersama sebagai entitas robot, dan menentukan sendiri urutan tindakan yang perlu dilakukan untuk menyelesaikan tugas yang diberikan. Dalam arti tertentu, sistem otonom adalah robot yang dapat menyelesaikan masalahnya sendiri.

Karena DIDO sangat umum sehingga para peneliti baik di bidang akademik maupun industri telah menemukan cara untuk menerapkan perangkat lunak untuk memecahkan berbagai masalah kontrol yang optimal. Kami melihat ini dengan jelas dalam robotika di mana peneliti dapat mengintegrasikan DIDO dengan perangkat lunak yang ada dalam sistem otonom. Pencipta DIDO, Ross, mengatakan dalam sebuah wawancara bahwa salah satu mantan muridnya secara khusus telah menerapkan perangkat lunak tersebut ke robot darat dengan beberapa hasil yang luar biasa. Itu sama Ph.D. lulusan telah meneliti navigasi beberapa kendaraan robot melalui perairan kasar tanpa mereka bertabrakan.

Bidang lain di mana DIDO mendapatkan daya tarik adalah aeronautika. Sebelumnya, kami memberikan contoh semua kondisi yang menentukan cara mengemudikan pesawat. Contoh itu tidak sembarangan: Kami memilihnya karena DIDO telah mampu melakukan hal itu. Selain membantu pencarian lintasan terbang pesawat layang, DIDO juga membantu optimalisasi bahan bakar pesawat. American Institute of Aeronautics and Astronautics (AIAA) telah menerbitkan studi dari para peneliti di seluruh dunia yang telah menggunakan DIDO dalam pekerjaan mereka.

Salah satu aplikasi unik DIDO telah menerapkan perhitungan kontrol optimalnya untuk mengemudikan glider bawah laut, sistem otonom tak berawak dalam bentuk kendaraan bawah air bersayap. Para peneliti di Virginia Tech mencari cara untuk memastikan glider seperti itu dapat bergerak seperti lumba-lumba melalui air, yang hemat energi dan berguna saat melakukan survei oseanografi. Salah satu tantangan tim adalah mengatasi efek macet saat melakukan transisi dari lintasan ke bawah ke atas. Tim melaporkan bahwa DIDO adalah metode solusi termudah bagi mereka untuk menyiapkan dan menjalankan penelitian mereka, meskipun mereka juga melaporkan mendapatkan perhitungan serupa dengan alat lain [sumber: Kraus, Cliff, Woolsey dan Luby ].

Sepanjang artikel ini, kita telah melihat apa itu masalah kontrol optimal, bagaimana DIDO membantu menyelesaikannya, dan cara inovatif para peneliti menerapkan DIDO di berbagai bidang komersial dan akademis. Optimalkan pengalaman DIDO Anda dengan melihat lebih banyak informasi di halaman berikutnya.

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