This paper focuses on the controller design using fuzzy sliding mode control (FSMC) with application to electro-mechanical brake (EMB) systems using BLDC Motor. The EMB controller transmits the control signal to the motor driver to rotate the motor. The torque distribution of motors is studied in this paper actually. Firstly, the model of the EMB system is established. Then the state observer is developed to estimate the vehicle states including the vehicle velocity and longitudinal force. Due to the fact that the EMB system is nonlinear and uncertain, a FSMC strategy based on wheel slip ratio is proposed, where both the normal and emergency braking conditions are taken into account. The equivalent control law of sliding mode controller is designed on the basis of the variation of the front axle and rear axle load during the brake process, while the switching control law is adjusted by the fuzzy corrector. The simulation results illustrate that the FSMC strategy has the superior performance, better adaptability to various types of roads, and shorter braking distance, as compared to PID control and traditional sliding mode control technologies. Finally, the hardware-in-loop (HIL) experimental results have exemplified the validation of the developed methodology.
A look-ahead algorithm is proposed to solve the online multiple workflow scheduling problem with two constraints in heterogeneous system. In this problem, workflows come to the system online when they are released, and each workflow is composed of multiple tasks which can be executed on heterogeneous processors, according to their types. Considered two constrains including the non-preemptive processor and the task order in a workflow, the proposed algorithm utilizes the information contained in the list of the submitted workflows and optimizes the scheduling of current task according to subsequent tasks. It can keep the subsequent tasks from waiting for a long time due to the occupation of the limited resource by the current task. The simulation results show that the proposed look-ahead algorithm outperforms four classical online scheduling algorithms, and the algorithm can get better performance when the look-ahead value L = 1 than L ≥ 2.
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