Adaptive iterative learning control of robotic system based on particle swarm optimization
Апстракт
In this paper, an adaptive iterative learning control algorithm for robotic manipulators is
proposed. A simplified robot manipulator model with 3 degrees of freedom is used as control
object for verification purposes. The mathematical model is obtained via Rodriguez approach for
modeling differential equations of motion for multi-body systems. The model itself is a simple
open-chain kinematic structure. The proposed control system design consists of two layers of
controllers. In the inner loop, feedback linearization is applied to deal with the model
nonlinearities. Post feedback linearization advanced iterative learning control (ILC) algorithm of
sign-D (signum-Derivative) type is introduced as feed-forward compensation with classical PD
(Proportional-Derivative) controller in feedback closed loop. A particle swarm optimization
(PSO) algorithm is used to optimize ILC gain parameters while gains for PD controller are set by
trial and error. Suitable cost function based on pos...ition error is chosen for PSO algorithm in order
to ensure convergence. Numerical simulation is carried out in two cases – case with constant
learning gains and case with PSO optimized learning gains. It is observed that the proposed
control law converges to some steady-state error value in both cases.
Кључне речи:
robot dynamics / feedback linearization / iterative learning control / PSO optimization / control designИзвор:
8th International Congress of Serbian Society of Mechanics, Kragujevac, Serbia, June 28-30 2021., 2021, 334-343Издавач:
- Beograd : Srpsko društvo za mehaniku
Финансирање / пројекти:
- Министарство науке, технолошког развоја и иновација Републике Србије, институционално финансирање - 200105 (Универзитет у Београду, Машински факултет) (RS-MESTD-inst-2020-200105)
- Министарство науке, технолошког развоја и иновација Републике Србије, институционално финансирање - 200066 (Лола институт, Београд) (RS-MESTD-inst-2020-200066)
Колекције
Институција/група
Mašinski fakultetTY - CONF AU - Zivković, Nikola Lj. AU - Lazarević, Mihailo AU - Petrović, Milica PY - 2021 UR - https://machinery.mas.bg.ac.rs/handle/123456789/4093 AB - In this paper, an adaptive iterative learning control algorithm for robotic manipulators is proposed. A simplified robot manipulator model with 3 degrees of freedom is used as control object for verification purposes. The mathematical model is obtained via Rodriguez approach for modeling differential equations of motion for multi-body systems. The model itself is a simple open-chain kinematic structure. The proposed control system design consists of two layers of controllers. In the inner loop, feedback linearization is applied to deal with the model nonlinearities. Post feedback linearization advanced iterative learning control (ILC) algorithm of sign-D (signum-Derivative) type is introduced as feed-forward compensation with classical PD (Proportional-Derivative) controller in feedback closed loop. A particle swarm optimization (PSO) algorithm is used to optimize ILC gain parameters while gains for PD controller are set by trial and error. Suitable cost function based on position error is chosen for PSO algorithm in order to ensure convergence. Numerical simulation is carried out in two cases – case with constant learning gains and case with PSO optimized learning gains. It is observed that the proposed control law converges to some steady-state error value in both cases. PB - Beograd : Srpsko društvo za mehaniku C3 - 8th International Congress of Serbian Society of Mechanics, Kragujevac, Serbia, June 28-30 2021. T1 - Adaptive iterative learning control of robotic system based on particle swarm optimization EP - 343 SP - 334 UR - https://hdl.handle.net/21.15107/rcub_machinery_4093 ER -
@conference{ author = "Zivković, Nikola Lj. and Lazarević, Mihailo and Petrović, Milica", year = "2021", abstract = "In this paper, an adaptive iterative learning control algorithm for robotic manipulators is proposed. A simplified robot manipulator model with 3 degrees of freedom is used as control object for verification purposes. The mathematical model is obtained via Rodriguez approach for modeling differential equations of motion for multi-body systems. The model itself is a simple open-chain kinematic structure. The proposed control system design consists of two layers of controllers. In the inner loop, feedback linearization is applied to deal with the model nonlinearities. Post feedback linearization advanced iterative learning control (ILC) algorithm of sign-D (signum-Derivative) type is introduced as feed-forward compensation with classical PD (Proportional-Derivative) controller in feedback closed loop. A particle swarm optimization (PSO) algorithm is used to optimize ILC gain parameters while gains for PD controller are set by trial and error. Suitable cost function based on position error is chosen for PSO algorithm in order to ensure convergence. Numerical simulation is carried out in two cases – case with constant learning gains and case with PSO optimized learning gains. It is observed that the proposed control law converges to some steady-state error value in both cases.", publisher = "Beograd : Srpsko društvo za mehaniku", journal = "8th International Congress of Serbian Society of Mechanics, Kragujevac, Serbia, June 28-30 2021.", title = "Adaptive iterative learning control of robotic system based on particle swarm optimization", pages = "343-334", url = "https://hdl.handle.net/21.15107/rcub_machinery_4093" }
Zivković, N. Lj., Lazarević, M.,& Petrović, M.. (2021). Adaptive iterative learning control of robotic system based on particle swarm optimization. in 8th International Congress of Serbian Society of Mechanics, Kragujevac, Serbia, June 28-30 2021. Beograd : Srpsko društvo za mehaniku., 334-343. https://hdl.handle.net/21.15107/rcub_machinery_4093
Zivković NL, Lazarević M, Petrović M. Adaptive iterative learning control of robotic system based on particle swarm optimization. in 8th International Congress of Serbian Society of Mechanics, Kragujevac, Serbia, June 28-30 2021.. 2021;:334-343. https://hdl.handle.net/21.15107/rcub_machinery_4093 .
Zivković, Nikola Lj., Lazarević, Mihailo, Petrović, Milica, "Adaptive iterative learning control of robotic system based on particle swarm optimization" in 8th International Congress of Serbian Society of Mechanics, Kragujevac, Serbia, June 28-30 2021. (2021):334-343, https://hdl.handle.net/21.15107/rcub_machinery_4093 .