This article proposes a novel real time bug like algorithm for performing a dynamic smooth path planning scheme for an articulated vehicle under limited and sensory reconstructed surrounding static environment. In the...
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This paper presents a particle filter for multiple target tracking. The main contribution of this work is in the proposed likelihood function accounting for the interactions between the objects. The filter likelihood ...
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The focus in this paper is on active fault diagnosis (AFD) in closed-loop sampleddata systems. Applying the same AFD architecture as for continuous-time systems does not directly result in the same set of closed-loop ...
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We give explicit analytic formulas for computing the L2 norm of a discrete-time generalised system whose rational transfer matrix function may be improper or polynomial. The norm is expressed in terms of solutions of ...
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A possible limitation of differentially flat systems stems from the possibility of gain singularities on open or closed regions of the flat output phase space. The evasion of control gain singularity poses an importan...
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A possible limitation of differentially flat systems stems from the possibility of gain singularities on open or closed regions of the flat output phase space. The evasion of control gain singularity poses an important theoretical problem even under the scope of Active Disturbance Rejection control. In this article, we illustrate an interesting example of controlling a singular flat system, the inertia wheel pendulum, using the combined benefits of ADR control and flatness as applied to a carefully chosen flat tangent linearization model of the singular system.
Drive cycle following is important for concept comparisons when evaluating vehicle concepts, but it can be time consuming to develop good driver models that can achieve accurate following of a specific velocity profil...
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Drive cycle following is important for concept comparisons when evaluating vehicle concepts, but it can be time consuming to develop good driver models that can achieve accurate following of a specific velocity profile. Here, a new approach is proposed where a simple driver model based on a PID controller is extended with an Iterative Learning control (ILC) algorithm. Simulation results using a nonlinear vehicle and control system model show that it is possible to achieve very good cycle following in a few iterations with little tuning effort. It is also possible to utilize the repetitive behavior in the drive cycle to accelerate the convergence of the ILC algorithm even further.
In order to enhance search ability and expedite convergence rate of the multi-objective evolutionary algorithm, a crossover based adaptive local search algorithm, which is suitable for single objective differential al...
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In electric and hybrid-electric vehicles, the inverter output voltage is limited by available DC-link voltage, which restricts the vehicle speed and acceleration. Therefore the fundamental component of the motor volta...
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ISBN:
(纸本)9781479917631
In electric and hybrid-electric vehicles, the inverter output voltage is limited by available DC-link voltage, which restricts the vehicle speed and acceleration. Therefore the fundamental component of the motor voltage should be increased by operating inverter in the six-step mode at high speeds. Although hysteresis based direct torque control (DTC) is a straightforward approach and has several advantages, this method cannot work in the six-step mode. In this paper a new hysteresis based DTC with over modulation ability for interior permanent magnet synchronous machines (IPMSM) is suggested. In this method, unlike the previously proposed methods, the calculation of the voltage vector or flux reference in different phase angles is not necessary. In the proposed method, the flux trajectory is changed by adjusting the non-switching area and modifying switching table, and thus a seamless transformation between high-frequency switching and six-step square wave is possible. Also in this paper, the dynamic model for an electric vehicle is developed which its traction motor is controlled by proposed DTC. The simulation results prove that the proposed method modify the vehicle performances, notably. These results show that the vehicle with proposed method has a higher top speed and better acceleration. Also it is shown, that the proposed method can improve the vehicle efficiency for various driving cycles. In addition the results confirm the torque discontinuity does not appear in the whole range of vehicle speed.
This paper makes contribution in the area of model based predictive control (MPC) and in particular examines to what extent structured optimisation dynamics can improve regions of attraction, performance and computati...
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The framework of an automatic discovery system for critical flowgates and security operation rules in the power grid is designed. Based on the real-time operation data of the power grid, the system is able to automati...
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The framework of an automatic discovery system for critical flowgates and security operation rules in the power grid is designed. Based on the real-time operation data of the power grid, the system is able to automatically find the critical flowgates adapted to the online operation state of the grid. By using the automatic learning method, the system can find the fine rules of critical flowgates as the security operation knowledge of the grid. The functions of the core modules of the system are described, including online automatic discovery of critical flowgates, online calculation of limit transmission capacity of critical flowgates, online generation of mass simulation samples, feature selection, automatic discovery of security operation rules of the power grid. The online application of the system has been realized in Guangdong power grid. The application effect shows that the system is able to generate the security operation knowledge fast enough and refresh it every 15 minutes for online application as required. Meanwhile, the knowledge is capable of not only covering the existing security operation knowledge formulated by experts offline, but also finding new knowledge adapted to the online power grid operation mode, while improving the power grid security and economy.
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