Analysis Of the Geometrical Framework on the Vehicle's Moving Stability Using Expert System Controller

Abdelmoniem, A.; Osama, A.; Abdelaziz, M.; Maged, S.A (2020). A path-tracking algorithm using predictive Stanley lateral controller. Int. J. Adv. Robot. pp, 19-33, Burgos, E.; Bhandari, S. (2016) Potential flow field navigation with virtual force field for UAS collision avoidance. In Proceedings of the 2016 International Conference on Unmanned Aircraft Systems (ICUAS), Arlington, VA, USA, 7–10 pp. 505–513 Cabezas-Olivenza, M.; Zulueta, E.; Sanchez-Chica, A.; Teso-fz-Betoño, (2021) A.; Fernandez- Gamiz, U. Dynamical Analysis of a Navigation Algorithm. pp, 9-31 Chang, L.; Shan, L.; Jiang, C.; Dai, Y. Reinforcement based mobile robot path planning with improved dynamic window approach in unknown environment. Auton. Robots 2021, Chen, Y., Chen, L., Wang, J., & Sun, Y. (2015). Vehicle lateral stability control is based on the integrated control of active front steering and direct yaw moment control. Vehicle System Dynamics, 53(3), 316-335. Danciu, A., Faur, M., Tar, J. K., & Iclodean, C. (2017). The influence of wheel alignment on vehicle dynamics. Procedia Engineering, 181, 1069–1074. Gao, W., Wang, L., Cheng, J., & Rakheja, S. (2013). Analysis and control of vehicle lateral stability with active front steering and differential braking. Vehicle System Dynamics, 51(12), 1785–1802. Gong, F.T., and J.Y. Wang, (2012). Research on weighted fuzzy fault diagnosis based on adaptive neural networks. Int. J. Digital Content Technol. Appl., 6: 118–124. Hedrick, K. J., & Zhang, W. B. (2012). Nonlinear control for vehicle lane-keeping with disturbance rejection. Vehicle System Dynamics, 50(1), 141–159. Henkel, C.; Xie, L.; Stol, K.; Xu, W. (2018) Power-minimization and energy-reduction autonomous navigation of an omnidirectional Mecanum robot via the dynamic window approach local trajectory planning. Int. J. Adv. Robot. 15, 1–12. Kim, S., Yi, K., & Sunwoo, M. (2016). A study on the influence of suspension geometry on vehicle dynamics using design experiments. International Journal of Automotive Technology, 17(2), 285-294. Maarif, A.; Rahmaniar, W.; Vera, M.A.M.; Nuryono, A.A.; Majdoubi, R.; Cakan, A (2012). Artificial Potential Field Algorithm for Obstacle Avoidance in UAV Quadrotor for Dynamic Environment. In Proceedings of the 2021 IEEE International Conference on Communication, Networks and Satellite (COMNETSAT), Rakheja, S., Langari, R., & Vaishya, M. (2018). Developments in Road Vehicle System Dynamics: Application of Vehicle Dynamics Concepts for the Development of Intelligent Vehicles. CRC Press. Tesfazgi, S. Lederer, A.; Hirche, S (2021). Inverse Reinforcement Learning: A Control Lyapunov Approach. In Proceedings of the 2021 60th IEEE Conference on Decision and Control (CDC), Austin, TX, USA, 14–17 ; pp. 3627–3632. Zhang, F You, S.; Diao, M.; Gao, L.; (2020,).; Wang, H. Target tracking strategy using deep deterministic policy gradient. Appl. Soft Comput. pp. 50–512 Zhang, L., Y.W. Shi, and L.Q. Ren, (2012). Humanoid extraction of abnormal engine sounds by using ICA-R and VANC. Proceedings of the International Conference on Systems and Informatics, May 19–20, 2012, Yantai, China, pp. 1687–1692. Zhang, W., (2011). Based on expert systems in automotive engine fault diagnosis, Master Thesis, Taiyuan University of Technology, Taiyuan, China. Zhu, Q., A.R. Huang, and J. Bao, (2010). Design and implementation of an automobile fault diagnosis expert system. J. Hubei Automotive Indus. Inst., 24: 70–74.