Robot’s end-effector behavior in the workspace of the obtained model against the real experiment for the regulation task using PID controller.

Robot’s end-effector behavior in the workspace of the obtained model against the real experiment for the regulation task using PID controller.

<p>Robot’s end-effector behavior in the workspace of the obtained model against the real experiment for the regulation task using PID controller.</p>

محفوظ في:
التفاصيل البيبلوغرافية
المؤلف الرئيسي: Roberto Castro-Medina (21484990) (author)
مؤلفون آخرون: Miguel Gabriel Villarreal-Cervantes (21484993) (author), Leonel Germán Corona-Ramírez (21484996) (author), Geovanni Flores-Caballero (21484999) (author), Alejandro Rodríguez-Molina (6506204) (author), Ramón Silva-Ortigoza (11421101) (author), Víctor Darío Cuervo-Pinto (21485002) (author), Andrés Abraham Palma-Huerta (21485005) (author)
منشور في: 2025
الموضوعات:
Medicine
Biotechnology
Ecology
Computational Biology
Space Science
Biological Sciences not elsewhere classified
Mathematical Sciences not elsewhere classified
Information Systems not elsewhere classified
thereby reducing risks
optimal parameterization obtained
robot &# 8217
particle swarm optimization
freedom serial robot
behavior closely resembles
model &# 8217
another electromechanical system
widely adopted due
particularly robotic ones
methodology &# 8217
developing control strategies
robot model demonstrated
inspired optimization techniques
mil simulation environment
model parameterization approach
dynamic model parameters
model parameterization
inspired optimization
dynamic parameters
robotic systems
particularly well
enables simulation
behavior accurately
simulated model
model characteristics
inspired algorithms
dynamic systems
conservative model
proposed approach
holistic approach
approach formulates
system design
real system
physical system
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work proposes
wide range
specialized real
realistic simulations
real plant
reaction force
proposed method
practical models
optimization problem
mil ),
inherent properties
hil ),
genetic algorithm
fully leverage
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