Control engineering
Related papers: 20
About
Control engineering is the branch of engineering concerned with designing systems that regulate, command, and direct the behavior of dynamic processes to achieve desired outcomes. In robotics and AI, it provides the mathematical and algorithmic foundations for making robots move accurately, respond to disturbances, and interact safely with their environment. Core techniques include feedback control—where sensor measurements are continuously compared against desired targets to correct errors—as well as more advanced methods such as adaptive control, sliding mode control, optimal control, and model-based feedforward compensation. These approaches govern everything from precise joint-level motion in robot manipulators to obstacle avoidance in mobile robots, force regulation during physical interaction, and coordinated behavior across multi-agent systems. Visual servoing, trajectory tracking, and biped locomotion all rely heavily on control engineering principles. The field matters because even the most mechanically capable or intelligently planned robot is only as effective as its control system allows—poor control leads to instability, imprecision, or unsafe behavior. Mastery of control engineering is therefore essential for anyone designing reliable, high-performance robotic and autonomous systems.
Top Researchers
Top Cited Papers
A robust layered control system for a mobile robot
Rodney A. Brooks
Citations: 7743 • 1986
Real-Time Obstacle Avoidance for Manipulators and Mobile Robots
Oussama Khatib
Citations: 7533 • 1986
Design, fabrication and control of soft robots
Daniela Rus, Michael T. Tolley
Citations: 5556 • 2015
Introduction to Robotics mechanics and Control
John Craig
Citations: 5039 • 1986
Robot dynamics and control
Mark W. Spong
Citations: 3821 • 1989
A tutorial on visual servo control
Seth Hutchinson, Gregory D. Hager, Peter Corke
Citations: 3499 • 1996
Bettering operation of Robots by learning
Suguru Arimoto, Sadao Kawamura, Fumio Miyazaki
Citations: 3445 • 1984
Sliding Mode Control in Electro-Mechanical Systems
Vadim Utkin, Jürgen Guldner, Jingxin Shi
Citations: 3211 • 2010
Hybrid Position/Force Control of Manipulators
Marc H. Raibert, John Craig
Citations: 2978 • 1981
A unified approach for motion and force control of robot manipulators: The operational space formulation
Oussama Khatib
Citations: 2917 • 1987
Robot Manipulators: Mathematics, Programming, and Control
Richard P. Paul
Citations: 2813 • 1981
Continuous finite-time control for robotic manipulators with terminal sliding mode
Shuanghe Yu, Xinghuo Yu, Bijan Shirinzadeh, Zhihong Man
Citations: 2605 • 2005
Manipulability of Robotic Mechanisms
Tsuneo Yoshikawa
Citations: 2516 • 1985
Robotics: modelling, planning and control
Bruno Siciliano, L. Sciavicco, Luigi Villani, Giuseppe Oriolo
Citations: 2507 • 2009
Fuzzy Control Systems Design and Analysis: A Linear Matrix Inequality Approach
Kazuo Tanaka, Hua O. Wang
Citations: 2454 • 2008
Visual servo control. I. Basic approaches
François Chaumette, Seth Hutchinson
Citations: 2431 • 2006
An Overview of Recent Progress in the Study of Distributed Multi-Agent Coordination
Yongcan Cao, Wenwu Yu, Wei Ren, Guanrong Chen
Citations: 2385 • 2012
On the Adaptive Control of Robot Manipulators
Jean-Jacques Slotine, Weiping Li
Citations: 2258 • 1987
An integrated design and fabrication strategy for entirely soft, autonomous robots
Michael Wehner, Ryan L. Truby, Daniel J. Fitzgerald, Bobak Mosadegh, George M. Whitesides, Jennifer A. Lewis, Robert J. Wood
Citations: 2096 • 2016
Biped walking pattern generation by using preview control of zero-moment point
Shuuji Kajita, Fumio Kanehiro, Kenji Kaneko, Kiyoshi Fujiwara, Kensuke Harada, Kazuhito Yokoi, Hirohisa Hirukawa
Citations: 2083 • 2004