Trajectory Control of Robotic Manipulator using Metaheuristic Algorithms
Robotic manipulators are extremely nonlinear complex and, uncertain systems. They have multi-input multi-output (MIMO) dynamics, which makes controlling manipulators difficult. Robotic manipulators have wide applications in many industries like processes, medicine, and space. Effective control of t...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Ram Arti Publishers
2023-04-01
|
| Series: | International Journal of Mathematical, Engineering and Management Sciences |
| Subjects: | |
| Online Access: | https://www.ijmems.in/cms/storage/app/public/uploads/volumes/16-IJMEMS-22-0674-8-2-264-281-2023.pdf |
| _version_ | 1811176852291584000 |
|---|---|
| author | Devendra Rawat Mukul Kumar Gupta Abhinav Sharma |
| author_facet | Devendra Rawat Mukul Kumar Gupta Abhinav Sharma |
| author_sort | Devendra Rawat |
| collection | DOAJ |
| description | Robotic manipulators are extremely nonlinear complex and, uncertain systems. They have multi-input multi-output (MIMO) dynamics, which makes controlling manipulators difficult. Robotic manipulators have wide applications in many industries like processes, medicine, and space. Effective control of these manipulators is extremely important to perform these industrial tasks. Researchers are working on the control of robotic manipulators using conventional and intelligent control methods. Conventional control methods are proportional integral and derivative (PID), Fractional order proportional integral and derivative (FOPID), sliding mode control (SMC), and optimal & robust control while intelligent control method includes Artificial Neural network (ANN), Fuzzy logic control (FLC) and metaheuristic optimization algorithms based control schemes. This paper presents the trajectory control of a robotic manipulator using a PID controller. Four different meta-heuristic algorithms namely Sooty tern optimization (STO), Spotted Hyena optimizer (SHO), Atom Search optimization (ASO), and Arithmetic Optimization algorithm (AOA) are used to optimize the gains of PID controller for trajectory control of a two-link robotic manipulator and a novel hybrid sooty tern and particle swarm optimization (STOPSO) has been designed. These optimization techniques are nature-inspired algorithms that give the optimal gain values while minimizing the performance indices. A performance index comprising Integral time absolute error (ITAE) having weights for both links has been considered to achieve the desired trajectory. These optimization techniques are stochastic in nature so statistical analysis and Freidman’s ranking test has been performed to evaluate the effectiveness of these algorithms. The proposed hybrid STOPSO provided a fitness value of 0.04541 and showed a standard deviation of 0.0002. A comparative study of these optimization techniques is presented and as a result, hybrid STOPSO provides the best results with minimum fitness value followed by STO, AOA, ASO, and SHO algorithms. |
| first_indexed | 2024-04-10T19:59:38Z |
| format | Article |
| id | doaj.art-c1db21d7fe064e5690de64ab3f4d43c6 |
| institution | Directory Open Access Journal |
| issn | 2455-7749 |
| language | English |
| last_indexed | 2024-04-10T19:59:38Z |
| publishDate | 2023-04-01 |
| publisher | Ram Arti Publishers |
| record_format | Article |
| series | International Journal of Mathematical, Engineering and Management Sciences |
| spelling | doaj.art-c1db21d7fe064e5690de64ab3f4d43c62023-01-27T13:07:16ZengRam Arti PublishersInternational Journal of Mathematical, Engineering and Management Sciences2455-77492023-04-0182264281https://doi.org/10.33889/IJMEMS.2023.8.2.016Trajectory Control of Robotic Manipulator using Metaheuristic AlgorithmsDevendra Rawat 0Mukul Kumar Gupta1Abhinav Sharma2Department of Electrical & Electronics Engineering, University of Petroleum and Energy Studies, Dehradun, Uttarakhand, India.Department of Electrical & Electronics Engineering, University of Petroleum and Energy Studies, Dehradun, Uttarakhand, India.Department of Electrical & Electronics Engineering, University of Petroleum and Energy Studies, Dehradun, Uttarakhand, India.Robotic manipulators are extremely nonlinear complex and, uncertain systems. They have multi-input multi-output (MIMO) dynamics, which makes controlling manipulators difficult. Robotic manipulators have wide applications in many industries like processes, medicine, and space. Effective control of these manipulators is extremely important to perform these industrial tasks. Researchers are working on the control of robotic manipulators using conventional and intelligent control methods. Conventional control methods are proportional integral and derivative (PID), Fractional order proportional integral and derivative (FOPID), sliding mode control (SMC), and optimal & robust control while intelligent control method includes Artificial Neural network (ANN), Fuzzy logic control (FLC) and metaheuristic optimization algorithms based control schemes. This paper presents the trajectory control of a robotic manipulator using a PID controller. Four different meta-heuristic algorithms namely Sooty tern optimization (STO), Spotted Hyena optimizer (SHO), Atom Search optimization (ASO), and Arithmetic Optimization algorithm (AOA) are used to optimize the gains of PID controller for trajectory control of a two-link robotic manipulator and a novel hybrid sooty tern and particle swarm optimization (STOPSO) has been designed. These optimization techniques are nature-inspired algorithms that give the optimal gain values while minimizing the performance indices. A performance index comprising Integral time absolute error (ITAE) having weights for both links has been considered to achieve the desired trajectory. These optimization techniques are stochastic in nature so statistical analysis and Freidman’s ranking test has been performed to evaluate the effectiveness of these algorithms. The proposed hybrid STOPSO provided a fitness value of 0.04541 and showed a standard deviation of 0.0002. A comparative study of these optimization techniques is presented and as a result, hybrid STOPSO provides the best results with minimum fitness value followed by STO, AOA, ASO, and SHO algorithms. https://www.ijmems.in/cms/storage/app/public/uploads/volumes/16-IJMEMS-22-0674-8-2-264-281-2023.pdftwo-link robotic manipulatoroptimization techniquespidstoshoasoaoa |
| spellingShingle | Devendra Rawat Mukul Kumar Gupta Abhinav Sharma Trajectory Control of Robotic Manipulator using Metaheuristic Algorithms International Journal of Mathematical, Engineering and Management Sciences two-link robotic manipulator optimization techniques pid sto sho aso aoa |
| title | Trajectory Control of Robotic Manipulator using Metaheuristic Algorithms |
| title_full | Trajectory Control of Robotic Manipulator using Metaheuristic Algorithms |
| title_fullStr | Trajectory Control of Robotic Manipulator using Metaheuristic Algorithms |
| title_full_unstemmed | Trajectory Control of Robotic Manipulator using Metaheuristic Algorithms |
| title_short | Trajectory Control of Robotic Manipulator using Metaheuristic Algorithms |
| title_sort | trajectory control of robotic manipulator using metaheuristic algorithms |
| topic | two-link robotic manipulator optimization techniques pid sto sho aso aoa |
| url | https://www.ijmems.in/cms/storage/app/public/uploads/volumes/16-IJMEMS-22-0674-8-2-264-281-2023.pdf |
| work_keys_str_mv | AT devendrarawat trajectorycontrolofroboticmanipulatorusingmetaheuristicalgorithms AT mukulkumargupta trajectorycontrolofroboticmanipulatorusingmetaheuristicalgorithms AT abhinavsharma trajectorycontrolofroboticmanipulatorusingmetaheuristicalgorithms |