58,244 research outputs found

    Smart Traction Control Systems for Electric Vehicles Using Acoustic Road-type Estimation

    Full text link
    The application of traction control systems (TCS) for electric vehicles (EV) has great potential due to easy implementation of torque control with direct-drive motors. However, the control system usually requires road-tire friction and slip-ratio values, which must be estimated. While it is not possible to obtain the first one directly, the estimation of latter value requires accurate measurements of chassis and wheel velocity. In addition, existing TCS structures are often designed without considering the robustness and energy efficiency of torque control. In this work, both problems are addressed with a smart TCS design having an integrated acoustic road-type estimation (ARTE) unit. This unit enables the road-type recognition and this information is used to retrieve the correct look-up table between friction coefficient and slip-ratio. The estimation of the friction coefficient helps the system to update the necessary input torque. The ARTE unit utilizes machine learning, mapping the acoustic feature inputs to road-type as output. In this study, three existing TCS for EVs are examined with and without the integrated ARTE unit. The results show significant performance improvement with ARTE, reducing the slip ratio by 75% while saving energy via reduction of applied torque and increasing the robustness of the TCS.Comment: Accepted to be published by IEEE Trans. on Intelligent Vehicles, 22 Jan 201

    Speeding up liquid crystal SLMs using overdrive with phase change reduction

    Get PDF
    Nematic liquid crystal spatial light modulators (SLMs) with fast switching times and high diffraction efficiency are important to various applications ranging from optical beam steering and adaptive optics to optical tweezers. Here we demonstrate the great benefits that can be derived in terms of speed enhancement without loss of diffraction efficiency from two mutually compatible approaches. The first technique involves the idea of overdrive, that is the calculation of intermediate patterns to speed up the transition to the target phase pattern. The second concerns optimization of the target pattern to reduce the required phase change applied to each pixel, which in addition leads to a substantial reduction of variations in the intensity of the diffracted light during the transition. When these methods are applied together, we observe transition times for the diffracted light fields of about 1 ms, which represents up to a tenfold improvement over current approaches. We experimentally demonstrate the improvements of the approach for applications such as holographic image projection, beam steering and switching, and real-time control loops

    CSI technology validation on an LSS ground experiment facility

    Get PDF
    The test bed developed at JPL for experimental evaluation of new technologies for the control of large flexible space structures is described. The experiment consists of a flexible spacecraft dynamic simulator, sensors, actuators, a microcomputer, and an advanced programming environment. The test bed has been operational for over a year, and thus far nine experiments were completed or are currently in progress. Several of these experiments were reported at the 1987 CSI conference, and several recent ones are documented in this paper, including high order adaptive control, non-parametric system identification, and mu-synthesis robust control. An aggressive program of experiments is planned for the forseeable future

    Control optimization, stabilization and computer algorithms for aircraft applications

    Get PDF
    The analysis and design of complex multivariable reliable control systems are considered. High performance and fault tolerant aircraft systems are the objectives. A preliminary feasibility study of the design of a lateral control system for a VTOL aircraft that is to land on a DD963 class destroyer under high sea state conditions is provided. Progress in the following areas is summarized: (1) VTOL control system design studies; (2) robust multivariable control system synthesis; (3) adaptive control systems; (4) failure detection algorithms; and (5) fault tolerant optimal control theory

    Empirical models, rules, and optimization

    Get PDF
    This paper considers supply decisions by firms in a dynamic setting with adjustment costs and compares the behavior of an optimal control model to that of a rule-based system which relaxes the assumption that agents are explicit optimizers. In our approach, the economic agent uses believably simple rules in coping with complex situations. We estimate rules using an artificially generated sample obtained by running repeated simulations of a dynamic optimal control model of a firm's hiring/firing decisions. We show that (i) agents using heuristics can behave as if they were seeking rationally to maximize their dynamic returns; (ii) the approach requires fewer behavioral assumptions relative to dynamic optimization and the assumptions made are based on economically intuitive theoretical results linking rule adoption to uncertainty; (iii) the approach delineates the domain of applicability of maximization hypotheses and describes the behavior of agents in situations of economic disequilibrium. The approach adopted uses concepts from fuzzy control theory. An agent, instead of optimizing, follows Fuzzy Associative Memory (FAM) rules which, given input and output data, can be estimated and used to approximate any non-linear dynamic process. Empirical results indicate that the fuzzy rule-based system performs extremely well in approximating optimal dynamic behavior in situations with limited noise.Decision-making. ,econometric models ,TMD ,
    corecore