Controller (irrigation)
Related papers: 20
About
A controller, in the context of robotics and AI, is a computational or algorithmic system that generates commands to drive a robot or automated system toward a desired state or behavior. Controllers process sensory inputs — such as position, force, velocity, or environmental feedback — and compute appropriate actuator outputs to minimize error between the current and target states. They appear across virtually every robotic application, from manipulator trajectory tracking and mobile robot navigation to quadrotor stabilization, biped locomotion, and wearable assistive devices. Control approaches range from classical feedback methods (PID, feedforward) to advanced techniques such as adaptive control, sliding mode control, fuzzy logic systems, neural network controllers, and optimization-based methods, each offering different trade-offs in robustness, adaptability, and computational cost. Controllers matter because they are the essential bridge between perception, planning, and physical action — without reliable control, even well-designed robots cannot execute tasks safely or accurately. As robots operate in increasingly unstructured, dynamic environments, sophisticated controllers that handle uncertainty, nonlinearity, and disturbances are critical to achieving dependable, real-world performance.
Top Researchers
Top Cited Papers
Hybrid Position/Force Control of Manipulators
Marc H. Raibert, John Craig
Citations: 2978 • 1981
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
Fuzzy Control Systems Design and Analysis: A Linear Matrix Inequality Approach
Kazuo Tanaka, Hua O. Wang
Citations: 2454 • 2008
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
Exact robot navigation using artificial potential functions
Elon Rimon, Daniel E. Koditschek
Citations: 1825 • 1992
Soft robotic glove for combined assistance and at-home rehabilitation
Panagiotis Polygerinos, Zheng Wang, Kevin C. Galloway, Robert J. Wood, Conor J. Walsh
Citations: 1580 • 2014
Zero Phase Error Tracking Algorithm for Digital Control
Masayoshi Tomizuka
Citations: 1470 • 1987
The Player/Stage Project: Tools for Multi-Robot and Distributed Sensor Systems
Brian Gerkey, Richard Vaughan, Andrew Howard
Citations: 1453 • 2003
Industrial applications of fuzzy control
道夫 菅野
Citations: 1450 • 1985
Disturbance Observer Based Control for Nonlinear Systems
Wen‐Hua Chen
Citations: 1423 • 2004
Stable adaptive teleoperation
G. Niemeyer, J.-J.E. Slotine
Citations: 1393 • 1991
Adaptive Control of Mechanical Manipulators
John Craig, Shankar Sastry
Citations: 1286 • 1987
Initial Experiments on the End-Point Control of a Flexible One-Link Robot
Robert H. Cannon, Eric Schmitz
Citations: 1143 • 1984
Multilayer neural-net robot controller with guaranteed tracking performance
Frank L. Lewis, Aydın Yeşildirek, Kai Liu
Citations: 1107 • 1996
Control of chained systems application to path following and time-varying point-stabilization of mobile robots
Claude Samson
Citations: 1061 • 1995
Control strategies for active lower extremity prosthetics and orthotics: a review
Michael R. Tucker, Jérémy Olivier, Anna Pagel, Hannes Bleuler, Mohamed Bouri, Olivier Lambercy, José del R. Millán, Robert Riener, Heike Vallery, Roger Gassert
Citations: 1053 • 2015
The attitude control problem
John T. Wen, Kenneth Kreutz-Delgado
Citations: 1053 • 1991
Adaptive manipulator control: A case study
J.-J.E. Slotine, Weiping Li
Citations: 1027 • 1988
Learning quadrupedal locomotion over challenging terrain
Citations: 1024 • 2020