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Direct Yaw Control of Vehicle using State Dependent Riccati Equation with Integral TermsSANDHU, F. , SELAMAT, H. , MAHALLEH, V. B. S.
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nonlinear equations, optimal control, quadratic programming, ricatti equation, sliding mode control
vehicle(33), control(33), system(18), dynamics(17), active(14), stability(9), steering(8), ling(7), integrated(6), systems(5)
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About this article
Date of Publication: 2016-05-31
Volume 16, Issue 2, Year 2016, On page(s): 101 - 110
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2016.02014
Web of Science Accession Number: 000376996100014
SCOPUS ID: 84974815457
Direct yaw control of four-wheel vehicles using optimal controllers such as the linear quadratic regulator (LQR) and the sliding mode controller (SMC) either considers only certain parameters constant in the nonlinear equations of vehicle model or totally neglect their effects to obtain simplified models, resulting in loss of states for the system. In this paper, a modified state-dependent Ricatti equation method obtained by the simplification of the vehicle model is proposed. This method overcomes the problem of the lost states by including state integrals. The results of the proposed system are compared with the sliding mode slip controller and state-dependent Ricatti equation method using high fidelity vehicle model in the vehicle simulation software package, Carsim. Results show 38% reduction in the lateral velocity, 34% reduction in roll and 16% reduction in excessive yaw by only increasing the fuel consumption by 6.07%.
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 FPGA-Based Implementation of Kalman Filter for Real-Time Estimation of Tire Velocity and Acceleration, Sandhu, Fargham, Selamat, Hazlina, Alavi, S. E., Behtaji Siahkal Mahalleh, Vahid, IEEE Sensors Journal, ISSN 1530-437X, Issue 17, Volume 17, 2017.
Digital Object Identifier: 10.1109/JSEN.2017.2726529 [CrossRef]
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Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania
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