Browsing by Subject "control system"

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    Nonlinear design, modeling and simulation of magneto rheological suspension: a control system and systems engineering approach
    (2017-12) Zambare, Hrishikesh B.; Razban, Ali; El-Mounayri, Hazim; Chen, Jie
    Suspension has been the most important subsystem of the vehicle viewed as a system. The ride comfort and vehicle handling performance are affected by the suspension design. Automotive technology has been continuously incorporating developments over the past few decades to provide the end users with a better comfort of driving. Multi-objective optimization of MR damper with objective function of maximizing damping force generated by MR damper with the geometrical parametric constraint function is achieved in this research using pattern search optimization technique. Research focuses on design, modeling, and simulation of active suspension using non-linear theory of the Magneto-Rheological (MR) damper with consideration of the hysteresis behavior for a quarter car model. The research is based on the assumption that each wheel experiences same disturbance excitation. Hysteresis is analyzed using Bingham, Dahl’s, and Bouc-Wen models. Research includes simulation of passive, Bingham, Dahl, and Bouc-wen models. Modeled systems are analyzed for the six road profiles, including road type C according to international standards ISO/TC108/SC2N67. Furthermore, the comparative study of the models for the highest comfort with less overshoot and settling time of vehicle sprung mass are executed. The Bouc-Wen model is 36.91 percent more comfortable than passive suspension in terms of damping force requirements and has a 26.16 percent less overshoot, and 88.31 percent less settling time. The simulation of the Bouc-Wen model yields a damping force requirement of 2003 N which is 97.63 percent in agreement with analytically calculated damping force generated by MR damper. PID controller implementation has improved the overshoot response of Bouc-Wen model in the range of 17.89 percent-81.96 percent for the different road profiles considered in this research without compromising on the settling time of system. PID controller implementation further improves the passenger comfort and vehicle ride handling capabilities. The interdisciplinary approach of systems engineering principles for the suspension design provides unique edge to this research. Classical systems engineering tools and MBSE approach are applied in the design of the MR damper. Requirement traceability successfully validates the optimized MR damper.
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    Selectively Decentralized Q-Learning
    (IEEE, 2017-10) Nguyen, Thanh; Mukhopadhyay, Snehasis; Computer and Information Science, School of Science
    In this paper, we explore the capability of selectively decentralized Q-learning approach in learning how to optimally stabilize control systems, as compared to the centralized approach. We focus on problems in which the systems are completely unknown except the possible domain knowledge that allow us to decentralize into subsystems. In selective decentralization, we explore all of the possible communication policies among subsystems and use the cumulative gained Q-value as the metric to decide which decentralization scheme should be used for controlling. The results show that the selectively decentralized approach not only stabilizes the system faster but also shows superior converging speed on gained Q-value in different systems with different interconnection strength. In addition, the selectively decentralized converging time does not seem to grow exponentially with the system dimensionality. Practically, this fact implies that the selectively decentralized Q-learning could be used as an alternative approach in large-scale unknown control system, where in theory, the Hamilton-Jacobi-Bellman-equation approach is difficult to derive the close-form solution.