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Modified GA Tuning IPD Control for a Single Tilt Tri-Rotors UAV


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DOI: https://doi.org/10.15866/irease.v11i1.12807

Abstract


In this article, the viability of a modified Genetic Algorithm (GA) is practiced to find the optimized Integral-Proportional-Derivative (I-PD) controller parameters. The benefits of the modified GA are generated and updated the new elite parameters in the short iteration of GA process, through that it can minimize the fitness function Integral of Absolute Error (IAE). This optimization methodology is then applied to a novel single tilt Tri-rotors attitude models. The proposed controller has demonstrated performance in the fast response, stability and less error.
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Keywords


Modified GA; IPD Control; Tri-Rotors; IAE

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References


Yang, Xin-She, Engineering Optimization: An Introduction with Metaheuristic Applications, (John Wiley&Sons, Inc. University of Cambridge, 2010).
http://dx.doi.org/10.1002/9780470640425

Haupt, Randy L. and Haupt, Sue Ellen, Practical Genetic Algorithms, 2ed. (John Wiley & Sons, Inc., 2004).
http://dx.doi.org/10.1002/0471671746

Grefenstette, J. J., Optimization of control parameters for genetic algorithms, IEEE Transactions on System, Man and Cybernetics (1986), 122-128.
http://dx.doi.org/10.1109/tsmc.1986.289288

Srinivas, M. and Patnaik, L., Adaptive probabilities of crossover and mutation in genetic algorithms, IEEE Transactions on System, Man and Cybernetics, vol. 24, no. 4, (1994), 656–667.
http://dx.doi.org/10.1109/21.286385

Harik, G., Learning linkage to efficiently solve problems of bounded difficulty using genetic algorithms. Ph.D. dissertation, Dept. Computer Science, University of Michigan, Ann Arbour, 1997.

Zlochin, M., Birattari, M., Meuleau, N., and Dorigo, M. Model-Based Search for Combinatorial Optimization: A Critical Survey, Annals of Operations Research, (2004).
http://dx.doi.org/10.1023/b:anor.0000039526.52305.af

Zhang, J., Chung, H. and Lo. W. L., Clustering-Based Adaptive Crossover and Mutation Probabilities for Genetic Algorithms, IEEE Transactions on Evolutionary Computation (2007) vol.11, no.3, 326–335.
http://dx.doi.org/10.1109/tevc.2006.880727

Coffin, D., Smith, R. E., Linkage Learning in Estimation of Distribution Algorithms. Linkage in Evolutionary Computation. Springer Berlin Heidelberg, 2008, 141–156.
http://dx.doi.org/10.1007/978-3-540-85068-7_7

Thierens, Dirk, The Linkage Tree Genetic Algorithm, Parallel Problem Solving from Nature, PPSN XI. Springer Berlin Heidelberg, 2010, 264–273.
http://dx.doi.org/10.1007/978-3-642-15844-5_27

Antunes A. P. and Azevedo J. L. F., Studies in Aerodynamic Optimization Based on Genetic Algorithms, Journal of Aircraft, Vol. 51, No. 3, (2014), 1002-1012.
http://dx.doi.org/10.2514/1.c032095

Mohammad Zadshakoyan, Vahid Pourmostaghimi, Cutting Tool Crater Wear Measurement in Turning Using Chip Geometry and Genetic Programming, International Journal of Applied Metaheuristic Computing, Vol. 6, Issue 1, (2015) 47-60.
http://dx.doi.org/10.4018/ijamc.2015010104

Mohammad Hamdan, Mohammad Hassan Abderrazzaq, Optimization of Small Wind Turbines using Genetic Algorithms, International Journal of Applied Metaheuristic Computing, Vol. 7, Issue 4, (2016), 50-65.
http://dx.doi.org/10.4018/ijamc.2016100104

Jian Tang, Jian Zhang, Zhiwei Wu, Zhuo Liu, Tianyou Chai, Wen Yu, Modeling collinear data using double-layer GA-based selective ensemble kernel partial least squares algorithm, Neurocomputing, Volume 219, (2017), 248-262.
http://dx.doi.org/10.1016/j.neucom.2016.09.019

Yoo, D.W., Oh, H.D., Won, D.Y. and Tahk, M.J., Dynamic modeling and control system design for Tri-Rotor UAV, Systems and Control in Aeronautics and Astronautics, (2010).
http://dx.doi.org/10.1109/isscaa.2010.5632868

Yoon, S., Lee, S.J., Lee, B., Kim, C.J., Lee, Y.J. and Sung, S., Design and flight test of a small Tri-rotor unmanned vehicle with a LQR based onboard attitude control system, International Journal of Innovative Computing, Information and Control, (2013), 2347-2360.
http://dx.doi.org/10.1109/ascc.2017.8287426

Cruz, S. S. and Lozano, R., Stabilization and Nonlinear Control for a novel Tri-rotor mini-aircraft, International Conference on Robotics and Automation, 2612-2617, (2005).
http://dx.doi.org/10.1109/robot.2005.1570507

Chiou, J.S., Tran, H.K., Peng, S.T., Attitude Control of a Single Tilt Tri-rotor UAV System: Dynamic Modeling and Each Channel Nonlinear Controllers Design, Journal of Mathematical Problems in Engineering, Article ID 275905, 6 pages, (2013).
http://dx.doi.org/10.1155/2013/275905

Sababha, B.H., Al Zu’bi, H.M. and Rawashdeh, O.A., A rotor-tilt-free tricopter UAV: design, modelling, and stability control, International Journal Mechatronics and Automation, Vol.5, (2015), 107–113.
http://dx.doi.org/10.1504/ijma.2015.075956

Tran, H. K., Chiou, J. S., and Peng, S. T., Design Genetic Algorithm Optimization Education Software based Fuzzy Controller for a Tricopter Fly Path Planning. EURASIA Journal of Mathematics, Science and Technology Education, 12(5),(2016), 1303-1312.
http://dx.doi.org/10.12973/eurasia.2016.1514a

Bouallegue, S., Khoud, K., Integral Backstepping Control Prototyping for a Quad Tilt Wing Unmanned Aerial Vehicle, International Review of Aerospace Engineering (IREASE), 9 (5), (2016), 152-161.
http://dx.doi.org/10.15866/irease.v9i5.10476

Skogestad, S., Simple analytic rules for model reduction and PID controller tuning, Journal of Process Control, Vol. 13, (2003) 291-309.
http://dx.doi.org/10.1016/s0959-1524(02)00062-8

Martins, F. G., Tuning PID Controllers using the ITAE Criterion” International Journal Engineering Education, (2005), 867-873.
http://dx.doi.org/10.1109/iccae.2010.5451484

Tan, W.; Liu, J.; Chen, T.; Marquez, H.J., Comparison of some well-known PID tuning formulas. Computation Chemical Engineering, (2006), 1416–1423.
http://dx.doi.org/10.1016/j.compchemeng.2006.04.001

Yongling Wu, Xiaodong Zhao, Kang Li, Min Zheng, Shaoyuan Li, Energy saving—Another perspective for parameter optimization of P and PI controllers. Neurocomputing, Vol. 174, (2016), 500-513.
http://dx.doi.org/10.1016/j.neucom.2015.05.124

Si Tayeb, M., Fizazi, H., A Dual-Level Hybrid Approach for Classification of Satellite Images, (2017) International Review of Aerospace Engineering (IREASE), 10 (1), pp. 42-49.
http://dx.doi.org/10.15866/irease.v10i1.11191

Kassem, A., El-Bayoumi, G., Habib, T., Kamalaldin, K., Improving Satellite Orbit Estimation Using Commercial Cameras, (2015) International Review of Aerospace Engineering (IREASE), 8 (5), pp. 174-178.
http://dx.doi.org/10.15866/irease.v8i5.8279

Eid, A., Abdel-Fadil, R., Abdel-Salam, M., Performance and Power Quality Improvements of MEA Power Distribution Systems using Model Predictive Control, (2017) International Review of Aerospace Engineering (IREASE), 10 (1), pp. 31-41.
http://dx.doi.org/10.15866/irease.v10i1.10998

Belhadri, K., Kouadri, B., Zegai, M., Adaptive Neural Control Algorithm Design for Attitude Stabilization of Quadrotor UAV, (2016) International Review of Automatic Control (IREACO), 9 (6), pp. 390-396.
http://dx.doi.org/10.15866/ireaco.v9i6.9919

Carloni, G., Bousson, K., A Nonlinear Control Method for Autonomous Navigation Guidance, (2016) International Review of Civil Engineering (IRECE), 7 (4), pp. 102-113.
http://dx.doi.org/10.15866/irece.v7i4.10757

Manzoor, M., Maqsood, A., Hasan, A., Quadratic Optimal Control of Aerodynamic Vectored UAV at High Angle of Attack, (2016) International Review of Aerospace Engineering (IREASE), 9 (3), pp. 70-79.
http://dx.doi.org/10.15866/irease.v9i3.8119


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