Multi-Objective Model Predictive Control for Vehicle Active Suspension System
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This paper puts forward a multi-objective model predictive control scheme in order to address the conflicting control objectives of a vehicle active suspension system. The key problem in designing an active suspension controller is that the controller has to realize a feasible control input that can satisfy the competing control requirements such as ride comfort, suspension travel and road handling. Hence, in this work, these constraints are integrated into an optimal control framework and a finite horizon model predictive controller is used to solve the multi-objective cost function. The key advantage of the proposed scheme is that the model predictive control design finds the optimal control input by solving the discrete time algebraic Riccati equation. This guarantees not only a robust closed loop system but also a realizable control effort, without violating the hard constraints of the active suspension system. The proposed model predictive control design is experimentally validated on a laboratory scale quarter car suspension system using hardware-in-loop testing. The performance of the model predictive control scheme is compared with the one of the unconstrained linear quadratic regulator and tested for four realistic road profiles. The experimental results substantiate that the suspension system controlled by the model predictive controller offers better ride comfort and road handling features when compared to the conventional linear quadratic regulator.
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S. Liun, H. Zhou, X. Luo, J. Xiao, Adaptive sliding fault tolerant control for nonlinear uncertain active suspension systems, Journal of the Franklin Institute, Vol. 353 (Issue 1): 180–199, 2016.
H. Pana, X. Jing, W. Sun, Robust finite-time tracking control for nonlinear suspension systems via disturbance compensation, Mechanical Systems and Signal Processing, Vol. 88: 49–61, 2017.
G.S. Prassad, M.K Mohan, A contemporary adaptive air suspension using LQR control for passenger vehicles, ISA Transactions, Vol. 93, 244-254, 2019.
S.A Chen, J.C Wang, M Yao, Y.B Kim, Improved optimal sliding mode control for a non-linear vehicle active suspension system, Journal of Sound and Vibration, Vol. 395: 1–25, 2017.
M.M Fateh, S.S. Alavi, Impedance control of an active suspension system, Mechatronics, Vol. 19 (Issue 1): 134–140, 2009.
W Sun, H Pan, Y Zhang, H Gao, Multi-objective control for uncertain nonlinear active suspension systems, Mechatronics, Vol. 24: (Issue 4): 318–327, 2014.
S.L Tung, Y.T Juang, W.H Lee, W.Y Shieh, W.Ying Wu, Optimization of the exponential stabilization problem in active suspension system using PSO, Expert Systems with Applications, Vol. 38 (Issue 11): 14044–14051, 2011.
R.R Das, VK Elumalai, R.G Subramanian, K.V.A Kumar, Adaptive predator–prey optimization for tuning of infinite horizon LQR applied to vehicle suspension system, Applied Soft Computing, Vol. 72: 518-526, 2018.
G. Wang, C. Chen, S. Yu, Robust non-fragile finite-frequency H1 static output-feedback control for active suspension systems, Mechanical Systems and Signal Processing, Vol. 91: 41–56, 2017.
Utkarsh S. Pusadkar, Sushant D. Chaudhari, P.D. Shendge, S.B. Phadke, Linear disturbance observer based sliding mode control for active suspension systems with non-ideal actuator, Journal of sound and vibration, Vol. 42: 428-444, 2019.
Yerrawar, R., Arakerimath, R., Taguchi Based Grey Relational Analysis Methodology for Semi Active Suspension System Using MR Damper, (2017) International Review of Mechanical Engineering (IREME), 11 (9), pp. 666-672.
H. Pan, W. Sun, X. Jing, H. Gao, J. Yao, Adaptive tracking control for active suspension systems with non-ideal actuators, Journal of sound and vibration, Vol. 399: 2-220, 2017.
Razdan, S., Bhave, S., Pathak, C., Awasare, P., Active Air Suspension for a Vehicle Based on Control of Air Mass Flow Rate, (2018) International Review of Mechanical Engineering (IREME), 12 (6), pp. 501-515.
D.Q. Mayne, Model predictive control: Recent developments and future promise, Automatica, Vol. 50 (Issue 12):2967-2986, 2014.
M. Khan, M. Tahiyat, S. Imtiaz, M.A.A.S.Choudhury, F. Khan, Experimental evaluation of control performance of MPC as a regulatory controller, ISA Transactions, Vol. 70: 512–520, 2017.
M. B. Saltik, L. Özkan, J.H.A. Ludlage, S. Weiland, P.M.J.V.D Hof, An outlook on robust model predictive control algorithms: Reflections on performance and computational aspects, Journal of Process Control, Vol. 61: 77–102, 2018.
D. Hrovat, S.D. Cairano, H.E.Tseng, I.V. Kolmanovsky, The Development of Model Predictive Control in Automotive Industry: A Survey, IEEE International Conference on Control Applications, October 3-5, Dubrovnik, Crotia, 2012.
J. A. Rossiter, Model Predictive Control: A Practical Approach (CRC Press, 2004).
Bemporad A., Morari M., Robust model predictive control: A survey. Robustness in identification and control. Lecture Notes in Control and Information Sciences, Vol. 245. (Springer, London, 1999).
D.E. Seborg, T.F. Edgar, D.A. Mellichamp, F.J. Doyle III, Process Dynamics and Control (Wiley, 2016).
Y. Ding, L. Wang, Y. Li, D. Li, Model predictive control and its application in agriculture: A review, Computers and Electronics in Agriculture, Vol. 151: 104–117, 2018.
A. Bemporad, M. Morari, V. Dua, E.N. Pistikopoulos, The explicit linear quadratic regulator for constrained systems, Automatica, Vol. 38 (Issue 1): 3-20, 2002.
Gaya, M., Bature, A., Yusuf, L., Madugu, I., Abubakar, U., Abubakar, S., Comparison of Control Strategies Applied to Nonlinear Quarterly Car Passive Suspension System, (2015) International Review of Automatic Control (IREACO), 8 (3), pp. 203-208.
El Malah, M., Ba-razzouk, A., Guisser, M., Abdelmounim, E., Madark, M., Bahri, H., Nonlinear Predictive Control for Maximum Power Point Tracking and Unity Power Factor of a Three Phase Grid Connected PV System, (2018) International Review of Automatic Control (IREACO), 11 (3), pp. 133-142.
Andang, A., Hartarti, R., Manuaba, I., Kumara, I., Harmonics Reduction on Electric Power Grid Using Shunt Hybrid Active Power Filter with Finite-Control-Set Model-Predictive Control, (2020) International Review on Modelling and Simulations (IREMOS), 13 (1), pp. 52-62.
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.
Mossa, M., Zaki Diab, A., Effective Model Predictive Control Approach for a Faulty Induction Motor Drive, (2019) International Review of Electrical Engineering (IREE), 14 (5), pp. 314-327.
Zaid, S., Albalawi, H., Application of Model Predictive Control to Ultra Sparse Matrix Rectifier, (2018) International Review of Electrical Engineering (IREE), 13 (5), pp. 357-364.
Mossa, M., Effective Predictive Flux Control for a Five Phase Induction Motor Drive with Inverter Output Filter, (2018) International Review of Electrical Engineering (IREE), 13 (5), pp. 373-384.
Okokpujie, K., Chukwu, E., Noma-Osaghae, E., Okokpujie, I., Novel Active Queue Management Scheme for Routers in Wireless Networks, (2018) International Journal on Communications Antenna and Propagation (IRECAP), 8 (1), pp. 52-61.
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