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Master of Science in Electrical and Computer Engineering (Non-Thesis) - Automatic Control

普渡大学

Purdue University

US美国

  • 学历文凭

    学历文凭

    Masters Degree

  • 专业院系

    专业院系

    School of Electrical and Computer Engineering

  • 开学时间

    开学时间

  • 课程时长

    课程时长

  • 课程学费

    课程学费

    汇率提示

国际学生入学条件

Applicants are ordinarily expected to hold a bachelor's degree from a college or university of recognized standing prior to registration.
Cumulative Grade Point Average from most recently conferred undergraduate, graduate, or professional degree: 3.25 or equivalent (A=4.0, Average GPA of admitted students is 3.6)
TOEFL iBT - 80 (Minimum Scores: Writing 22, Speaking 18, Listening 14 and Reading 19)
TOEFL PBT (overall score is no longer reported) - Reading 19, Listening 14 and Writing 22
IELTS - An overall band score of 6.5 is required for admission with the following minimum section requirements:
Reading 6.5, Listening 6.0, Speaking 6.0 and Writing 6.0
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  • 雅思总分:6.5
  • 托福网考总分:80
  • 托福笔试总分:160
  • 其他语言考试:NA

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课程简介

The field of Automatic Control (AC) studies how to make systems behave in a desired manner using feedback mechanisms and proper controller designs. Automatic Control plays a critical role in almost every aspect of our daily lives, including in home appliances, automobiles, aircraft, biomedical devices, manufacturing systems, the power grid, robots, and autonomous vehicles.<br><br>The AC area in the School of Electrical and Computer Engineering has a long history of major contributions to servomechanisms, manufacturing, automation, and space exploration. In this era of the Internet and information technology, AC faculty are addressing challenging control problems in systems with mobility and autonomy capabilities such as large robotic swarms and automated transportation systems, smart homes and cities, humanoid robots, and unmanned systems in the air, land, and sea. Tackling these complex systems requires research and education in innovative algorithms for coordination and control of large-scale systems, machine-learning techniques for perception and cognition capabilities that allow the systems to adapt to unstructured/unknown environments, and game-theoretic approaches to ensuring security and reliability. The AC faculty look forward to working with enthusiastic and highly motivated students to solve these challenging problems.
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