HGAPSO-Based Third Order-SMC, ST-SMC, and SMC Strategy for AAV Control: A Comparative Analysis
The study of the control of quadrotors was addressed extensively in different AAV research areas. In this work, the nonlinear dynamic model of the quadrotor has been developed using the Newton-Euler technique. By considering the system’s under-actuated and strongly coupled characteristics...
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2025-01-01
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| author | Dawit Kefale Wassie Lebsework Negash Lemma Abrham Tadesse Kassie |
| author_facet | Dawit Kefale Wassie Lebsework Negash Lemma Abrham Tadesse Kassie |
| author_sort | Dawit Kefale Wassie |
| collection | DOAJ |
| description | The study of the control of quadrotors was addressed extensively in different AAV research areas. In this work, the nonlinear dynamic model of the quadrotor has been developed using the Newton-Euler technique. By considering the system’s under-actuated and strongly coupled characteristics, the controllers have been then designed. As a main objective, design and comparative analysis of conventional sliding mode controller (SMC), supper twisting sliding mode controller (ST-SMC), and third order sliding mode controller (TO-SMC) schemes are realized for a nonlinear model of a quadrotor. The controller’s performance is highly dependent on the sliding surface coefficients and the controller constants. Therefore, a hybrid type of Genetic Algorithm (GA) and Particle Swarm Optimization (PSO), HGAPSO, has been formulated to find the best controllers’ parameters. The effectiveness of GA, PSO, and HGAPSO are investigated with TO-SMC in terms of trajectory tracking and robustness. The control algorithms are focused on the position, altitude, and attitude states manipulated by four control inputs. The performance comparison of the controllers is evaluated under the effect of wind disturbance. Model development and simulation of the proposed system are carried out using MATLAB Simulink and a set of simulations are conducted to illustrate the states and analysis the performance of the proposed controllers. Finally, the HGAPSO tuned TO-SMC has performance supremacy in trajectory tracking, chattering elimination, settling time, rise time, ITAE minimization, and robustness over HGAPSO tuned ST-SMC and SMC. In addition, the HGAPSO reveals attractive performance over PSO and GA alone. |
| format | Article |
| id | doaj-art-280e073cfd28481a93fd32d789ca43b2 |
| institution | DOAJ |
| issn | 2169-3536 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IEEE |
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| spelling | doaj-art-280e073cfd28481a93fd32d789ca43b22025-08-20T02:48:17ZengIEEEIEEE Access2169-35362025-01-0113528215284010.1109/ACCESS.2025.355314610935310HGAPSO-Based Third Order-SMC, ST-SMC, and SMC Strategy for AAV Control: A Comparative AnalysisDawit Kefale Wassie0Lebsework Negash Lemma1https://orcid.org/0000-0002-3288-7537Abrham Tadesse Kassie2https://orcid.org/0000-0001-7483-3994Faculty of Electrical and Computer Engineering, Bahir Dar Institute of Technology, Bahir Dar University, Bahir Dar, EthiopiaSchool of Electrical and Computer Engineering, Addis Ababa University, Addis Ababa, EthiopiaFaculty of Electrical and Computer Engineering, Bahir Dar Institute of Technology, Bahir Dar University, Bahir Dar, EthiopiaThe study of the control of quadrotors was addressed extensively in different AAV research areas. In this work, the nonlinear dynamic model of the quadrotor has been developed using the Newton-Euler technique. By considering the system’s under-actuated and strongly coupled characteristics, the controllers have been then designed. As a main objective, design and comparative analysis of conventional sliding mode controller (SMC), supper twisting sliding mode controller (ST-SMC), and third order sliding mode controller (TO-SMC) schemes are realized for a nonlinear model of a quadrotor. The controller’s performance is highly dependent on the sliding surface coefficients and the controller constants. Therefore, a hybrid type of Genetic Algorithm (GA) and Particle Swarm Optimization (PSO), HGAPSO, has been formulated to find the best controllers’ parameters. The effectiveness of GA, PSO, and HGAPSO are investigated with TO-SMC in terms of trajectory tracking and robustness. The control algorithms are focused on the position, altitude, and attitude states manipulated by four control inputs. The performance comparison of the controllers is evaluated under the effect of wind disturbance. Model development and simulation of the proposed system are carried out using MATLAB Simulink and a set of simulations are conducted to illustrate the states and analysis the performance of the proposed controllers. Finally, the HGAPSO tuned TO-SMC has performance supremacy in trajectory tracking, chattering elimination, settling time, rise time, ITAE minimization, and robustness over HGAPSO tuned ST-SMC and SMC. In addition, the HGAPSO reveals attractive performance over PSO and GA alone.https://ieeexplore.ieee.org/document/10935310/HGAPSOGAPSOquadrotorSMCST-SMC |
| spellingShingle | Dawit Kefale Wassie Lebsework Negash Lemma Abrham Tadesse Kassie HGAPSO-Based Third Order-SMC, ST-SMC, and SMC Strategy for AAV Control: A Comparative Analysis IEEE Access HGAPSO GA PSO quadrotor SMC ST-SMC |
| title | HGAPSO-Based Third Order-SMC, ST-SMC, and SMC Strategy for AAV Control: A Comparative Analysis |
| title_full | HGAPSO-Based Third Order-SMC, ST-SMC, and SMC Strategy for AAV Control: A Comparative Analysis |
| title_fullStr | HGAPSO-Based Third Order-SMC, ST-SMC, and SMC Strategy for AAV Control: A Comparative Analysis |
| title_full_unstemmed | HGAPSO-Based Third Order-SMC, ST-SMC, and SMC Strategy for AAV Control: A Comparative Analysis |
| title_short | HGAPSO-Based Third Order-SMC, ST-SMC, and SMC Strategy for AAV Control: A Comparative Analysis |
| title_sort | hgapso based third order smc st smc and smc strategy for aav control a comparative analysis |
| topic | HGAPSO GA PSO quadrotor SMC ST-SMC |
| url | https://ieeexplore.ieee.org/document/10935310/ |
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