References
- Elmi Z, Elmi S. Autonomous vehicle path planning using MPC and APF. In: Martínez García EA, editor. Motion Planning. Intechopen, 2022.
- Ko C, Han S, Choi M, et al. Integrated path planning and tracking control of autonomous vehicle for collision avoidance based on model predictive control and potential field. 2020 20th International Conference on Control, Automation and Systems (ICCAS). 2020. doi:10.23919/ICCAS50221.2020.9268369
- Hasegawa T, Pongsathorn R, Yamasaki A, et al. Study on autonomous driving intelligence system by using optimal control considering risk potential. Trans Soc Automot Eng Japan. 2015;46(2):497–502. doi:10.11351/jsaeronbun.46.497
- Liu C, Lee S, Varnhagen S, et al. Path planning for autonomous vehicles using model predictive control. IEEE Intelligent Vehicles Symposium (IV). 2017. doi:10.1109/IVS.2017.7995716
- Saitou Y, Imura J-I. An M-matrix based efficient algorithm for model predictive control of input constrained linear systems. The Soc Instru Control Eng. 2004;40(9):906–914.
- Camacho EF. Constrained generalized predictive control. IEEE Trans Automat Contr. 1993;38(2):327–332. doi: 10.1109/9.250485
- Luo Y, Serrani A, Yurkovich S, et al. Model predictive dynamic control allocation with actuator dynamics. Proc Am Control Confer. 2004;2:1695–1700. doi:10.23919/ACC.2004.1386823
- Peng H, Li F, Zhang S, et al. A novel fast model predictive control with actuator saturation for large-scale structures. Comput Struct. 2017;187:35–49. doi: 10.1016/j.compstruc.2017.03.014
- Wright SJ. Applying new optimization algorithms to model predictive control. Chem Process Control-V. 1997;93(316):147–155.
- Okawa I, Nonaka K. Comparative evaluation of a trajectory generator for obstacle avoidance guaranteeing computational upper cost. Int J Automot Eng. 2018;9(2):39–47. doi: 10.20485/jsaeijae.9.2_39
- Okawa I, Nonaka K. Linear complementarity model predictive control with limited iterations for box-constrained problems. Automatica. 2021;125:109429. doi: 10.1016/j.automatica.2020.109429
- Stine CR, Adegbege AA. Polynomially bounded linear complementarity problem-based solvers for model predictive control. IFAC-PapersOnLine. 2021;54(21):67–72. doi: 10.1016/j.ifacol.2021.12.012
- Pang J-S. On discovering hidden Z-matrices. In: Coffman CV and Fix GJ, editors, Constructive approaches to mathematical models. p. 231-241. New York: Academic Press; 1979.
- Kawaguchi N, Okawa I, Nonaka K. Linear complementarity model predictive control applied to vehicle steering experiment. SICE Annual Conference. 2022.
- Cottle RW, Pang J-S, Stone RE. The linear complementarity problem. Boston: Academic Press; 1992.
- Pang J-S, Chandrasekaran R. Linear complementarity problems solvable by a polynomially bounded pivoting algorithm. In Cottle RW, editors. Mathematical programing essays in honor of George B. Dantzig Part II. p. 13-27. Berlin: Springer; 1985.
- Maki R, Okawa I, Nonaka K. Stochastic model predictive obstacle avoidance with velocity reduction in accordance with chance constraints in crowded environments. Int J Auto Eng. 2022;13(3):114–121. doi:10.20485/jsaeijae.13.3_114