Control theory (sociology)
Related papers: 20
About
Control theory is a branch of applied mathematics and engineering that provides systematic methods for designing systems that regulate the behavior of dynamic processes. In robotics and AI, it forms the mathematical backbone for making robots move accurately, stably, and safely. By modeling how a robot's joints, forces, and velocities evolve over time, control theory enables engineers to design feedback loops that continuously correct errors between a robot's actual and desired states. Techniques such as PID control, sliding mode control, adaptive control, and model predictive control are routinely applied to manipulators, mobile robots, and bipedal walkers to achieve precise trajectory tracking, force regulation, and obstacle avoidance. Advanced formulations handle nonlinear dynamics, external disturbances, and uncertain parameters, while learning-based extensions allow robots to improve performance through experience. Control theory matters because without it, even a mechanically perfect robot would be unable to perform reliable, repeatable tasks—it is the discipline that translates physical hardware and computational intelligence into purposeful, governed motion.
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Top Cited Papers
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
Citations: 18993 • 1991
Real-Time Obstacle Avoidance for Manipulators and Mobile Robots
Oussama Khatib
Citations: 7533 • 1986
Introduction to Robotics mechanics and Control
John Craig
Citations: 5039 • 1986
Robot dynamics and control
Mark W. Spong
Citations: 3821 • 1989
Bettering operation of Robots by learning
Suguru Arimoto, Sadao Kawamura, Fumio Miyazaki
Citations: 3445 • 1984
Robot Modeling and Control
Mark W. Spong, Seth Hutchinson, M. Vidyasagar
Citations: 3281 • 2006
Randomized Kinodynamic Planning
Steven M. LaValle, James Kuffner
Citations: 3241 • 2001
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
Adaptive representation of dynamics during learning of a motor task
Reza Shadmehr, FA Mussa-Ivaldi
Citations: 2666 • 1994
Continuous finite-time control for robotic manipulators with terminal sliding mode
Shuanghe Yu, Xinghuo Yu, Bijan Shirinzadeh, Zhihong Man
Citations: 2605 • 2005
Robust Adaptive Control of Feedback Linearizable MIMO Nonlinear Systems With Prescribed Performance
Charalampos P. Bechlioulis, George A. Rovithakis
Citations: 2576 • 2008
Manipulability of Robotic Mechanisms
Tsuneo Yoshikawa
Citations: 2516 • 1985
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
On the Adaptive Control of Robot Manipulators
Jean-Jacques Slotine, Weiping Li
Citations: 2258 • 1987
Series elastic actuators
Gill A. Pratt, Matthew M. Williamson
Citations: 2177 • 2002
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