Abstract
This study compares the performances of the GA-FOPID and MOGA-FOPID controllers, which are fractional-order proportional–integral–derivative (FOPID) controllers tuned using genetic algorithm and multiple-objective genetic algorithm for position tracking accuracy of robotic manipulator, respectively. The tuning process of six control gains in the three FOPID controllers is technically challenging to achieve high position accuracy of robotic manipulator. This study is performed to objectively assess the performances of genetic algorithm and multiple-objective genetic algorithm in tuning the six control gains in the FOPID controller. From the simulation study, it is interesting to note that the GA-FOPID and MOGA-FOPID controllers produce approximately 8.2990 and 14.6307% reductions of the mean square error in the angular position accuracy response of robotic manipulator as compared with the GA-PID controller. It is envisaged that the GA-FOPID and MOGA-FOPID controllers can be useful in designing effective position tracking accuracy of robotic manipulators.
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Abbreviations
- \(U\left( s \right)\) :
-
Control signal of the FOPID control
- \(e\left( t \right)\):
-
Error between the desired angular position accuracy and
- \(E\left( s \right)\):
-
Error in the s-domain
- \(e\):
-
Exponential function
- \(i_{\max }\):
-
Maximum number of iteration
- MSE:
-
Mean square error
- PO:
-
Percentage of overshoot
- UDP:
-
Percentage of undershooting
- \(T_{{\text{r}}} \left( s \right)\):
-
Rise time
- \(T_{{\text{s}}} \left( s \right)\):
-
Settling time
- \(n\):
-
Number of parameters
- \(K_{{\text{p}}}\):
-
Proportional gain
- \(K_{{\text{i}}}\):
-
Integral gain
- \(K_{{\text{d}}}\):
-
Derivative gain
- \(\lambda\):
-
Lambda (non-integer order in derivative)
- \(\mu\):
-
Miu (non-integer order in derivative)
- DOF:
-
Degree of Freedom
- CTC:
-
Computed Torque Controller
- FOPID:
-
Fractional Order Proportional Integral Derivatives controller
- GA:
-
Genetic Algorithm
- GA-PID:
-
PID controller Tuned using GA
- GA-FOPID:
-
FOPID controller Tuned using GA
- NN:
-
Neural Network
- MOGA:
-
Multi-Objective Genetic Algorithm
- MOGA-FOPID:
-
FOPID controller Tuned using MOGA
- PID:
-
Proportional Integral Derivatives controller
- PSO:
-
Particle Swarm Optimization
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Acknowledgements
This study was funded by Universiti Putra Malaysia (UPM) through GP-IPM/2022/9712700.
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Hambali, N.F. et al. (2024). Tuning of FOPID Controller for Robotic Manipulator Using Genetic and Multiple-Objective Genetic Algorithms. In: Mohd. Isa, W.H., Khairuddin, I.M., Mohd. Razman, M.A., Saruchi, S.'., Teh, SH., Liu, P. (eds) Intelligent Manufacturing and Mechatronics. iM3F 2023. Lecture Notes in Networks and Systems, vol 850. Springer, Singapore. https://doi.org/10.1007/978-981-99-8819-8_47
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