Increased environmental awareness and skyrocketing fuel prices have pressed researchers and engineers to find energy efficient alternatives to traditional approaches. A novel steer-by-wire technology, which is based on pump displacement control actuation, has been proposed by the authors and was shown to improve the fuel efficiency of a wheel loader steering system by 43.5%. Building on this realization, the work in this paper deals with designing an adaptive velocity controller, which takes the form of an indirect self-tuning regulator that has the facility to cope with parametric uncertainties and uncertain nonlinearities associated with hydraulically actuated systems. The indirect self-tuning regulator algorithm is selected given that the uncertain plant parameters are estimated in the process, which is a useful byproduct that gives insight into system properties that will be considered in future investigation. Furthermore, a discrete adaptive control law with low computational cost is required for the application on hand. The designed self-tuning regulator and the estimation algorithm were validated in numerical simulations as well as experimentally on a designated prototype test vehicle, demonstrating the effectiveness of the proposed adaptive scheme in the face of uncertainties. The controller was able to adapt to varying load mass and inertia, which correlate to varying operating conditions that influence the system dynamics. Hence, besides offering improved fuel efficiency, the new steering technology also results in smarter machines.
An Indirect Adaptive Velocity Controller for a Novel Steer-by-Wire System
Contributed by the Dynamic Systems Division of ASME for publication in the JOURNAL OF DYNAMIC SYSTEMS, MEASUREMENT, AND CONTROL. Manuscript received November 25, 2013; final manuscript received March 7, 2014; published online June 12, 2014. Assoc. Editor: Gregory Shaver.
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Daher, N., and Ivantysynova, M. (June 12, 2014). "An Indirect Adaptive Velocity Controller for a Novel Steer-by-Wire System." ASME. J. Dyn. Sys., Meas., Control. September 2014; 136(5): 051012. https://doi.org/10.1115/1.4027172
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