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Energy-Efficient Control Allocation ...

Chen, Yan.

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Energy-Efficient Control Allocation for Over-Actuated Systems with Applications to Electric Ground Vehicles.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Energy-Efficient Control Allocation for Over-Actuated Systems with Applications to Electric Ground Vehicles./
作者:	Chen, Yan.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2013,
面頁冊數:	163 p.
附註:	Source: Dissertation Abstracts International, Volume: 76-05(E), Section: B.
Contained By:	Dissertation Abstracts International76-05B(E).
標題:	Mechanical engineering. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3670681
ISBN:	9781321476170

Energy-Efficient Control Allocation for Over-Actuated Systems with Applications to Electric Ground Vehicles.
Chen, Yan.

Energy-Efficient Control Allocation for Over-Actuated Systems with Applications to Electric Ground Vehicles. - Ann Arbor : ProQuest Dissertations & Theses, 2013 - 163 p.

Source: Dissertation Abstracts International, Volume: 76-05(E), Section: B.

Thesis (Ph.D.)--The Ohio State University, 2013.

This dissertation addresses a thorough investigation and development on general problem formulations, control/optimization algorithm designs, and experimental validations of energy-efficient control allocation (EECA), with application to an over-actuated pure electric ground vehicle (EGV) with four independent in-wheel motors.

ISBN: 9781321476170Subjects--Topical Terms:

649730
Mechanical engineering.

Energy-Efficient Control Allocation for Over-Actuated Systems with Applications to Electric Ground Vehicles.
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500 $a Adviser: Junmin Wang.
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520 $a This dissertation addresses a thorough investigation and development on general problem formulations, control/optimization algorithm designs, and experimental validations of energy-efficient control allocation (EECA), with application to an over-actuated pure electric ground vehicle (EGV) with four independent in-wheel motors.
520 $a For single-mode actuators which have only one working mode, either consuming or gaining energy, the existing CA scheme for over-actuated systems, which is usually in the form of different kinds of optimization problems, is extended to the EECA scheme by explicitly introducing efficiency functions of actuators as a portion of the power consumption expressions into the cost function. For dual-mode actuators which can work in both power-consuming and power-gaining modes, though not simultaneously, a virtual actuator concept and the corresponding compatibility condition is introduced to complete the novel EECA design frame in a general manner.
520 $a Based on the proposed EECA scheme, different optimization algorithms with various characteristics are developed for the EGV in order to achieve real-time implementations. For the vehicle longitudinal motion control, since the front and rear two in-wheel motors of the EGV can be lumped together as two pairs, a Karush-Kuhn-Tucker (KKT)-based EECA algorithm is proposed to find all the local optimal solutions, and consequently the global minimum through a further simple comparison among all the realistic local minima and boundary values for a non-convex optimization problem. The KKT-based algorithm is also independent on the selections of initial conditions by transferring the standard nonlinear optimization problem into classical eigenvalue problems. Consequently, the KKT-based algorithm is real-time implementable and is validated through both Simulink-CarSimRTM co-simulations and experimental results.
520 $a Since the computational load will exponentially grow along with the increase of the number of actuators, the KKT-based algorithm is not suitable for the planar motion control of the EGV, in which four independent in-wheel motors are applied. Thus, an adaptive EECA, which introduces a proper Lagrangian function into the Lyapunov approach, is designed to tackle the real-time implementation challenge for the EGV planar motion control. In the adaptive EECA, the control distribution can be dictated to gradually converge to the energy-optimal operating points without solving the complicated nonlinear or non-convex optimization problem at every instantaneous sample time. Moreover, taking allocation errors between virtual control efforts and real actuation realizations as inputs, the input-to-state stability of the overall feedback system is proved.
520 $a Simulation and experimental results from a four-wheel independently-actuated in-wheel motor electric vehicle also validated the effectiveness of the abovementioned EECA method.
590 $a School code: 0168.
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