A General Framework for Optimal Tuning of PID-like Controllers for Minimum Jerk Robotic Trajectories

The minimum jerk principle is commonly used for trajectory planning of robotic manipulators. However, since this principle is stated in terms of the robot’s kinematics, there is no guarantee that the joint controllers will actually track the planned acceleration and jerk profiles because the tuning...

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Bibliographic Details
Published in:Journal of intelligent & robotic systems Vol. 99; no. 3-4; pp. 467 - 486
Main Authors: Oliveira, Phelipe W., Barreto, Guilherme A., Thé, George A. P.
Format: Journal Article
Language:English
Published: Dordrecht Springer Netherlands 01.09.2020
Springer
Springer Nature B.V
Subjects:
Accuracy
Algorithms
Artificial Intelligence
Control
Control algorithms
Controllers
Electrical Engineering
Engineering
Kinematics
Mathematical optimization
Mechanical Engineering
Mechatronics
Optimization
Particle swarm optimization
Performance indices
Proportional integral derivative
Robot arms
Robot dynamics
Robot learning
Robotics
Robots
Tracking
Tracking control
Trajectory planning
Tuning
Performance indices
Fractional PID controller
Minimum jerk principle
Robot control
Particle swarm optimization
ISSN:0921-0296, 1573-0409
Online Access:Get full text
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Summary:The minimum jerk principle is commonly used for trajectory planning of robotic manipulators. However, since this principle is stated in terms of the robot’s kinematics, there is no guarantee that the joint controllers will actually track the planned acceleration and jerk profiles because the tuning of the controllers’ gains is decoupled from the trajectory planning. Bearing this in mind, in this paper we introduce a comprehensive framework for optimal estimation of the gains of PID-like controllers for tracking minimum-jerk (MJ) robot trajectories. The proposed methodology relies mainly on a novel variant of error-based performance indices (ISE, ITSE, IAE and ITAE) which are adapted to the tracking of MJ trajectories. Furthermore, the particle swarm optimization (PSO) algorithm is used to search for optimal values for the gains of the controllers of all joints simultaneously. The resulting approach is much simpler than recent developments based on more complex performance indices, in which joint controllers were individually optimized. The proposed approach is general enough to easily encompass the tuning of fractional PID controllers and a comprehensive set of experiments are reported comparing the performances of standard and fractional PID controllers for the task of interest.
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ISSN:0921-0296
1573-0409
DOI:10.1007/s10846-019-01121-y