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Model predictive control under timing constraints induced by controller area networks

机译:控制器局域网在时序约束下的模型预测控制

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When multiple model predictive controllers are implemented on a shared controller area network (CAN), their performance may degrade due to the variable timing and delays among messages. The priority based real-time scheduling of messages on the CAN introduces complex timing of events, especially when the types and number of messages change at runtime. This paper introduces a novel hybrid timing model to make runtime predictions on the timing of the messages for a finite time window. Controllers can be designed using the optimization algorithms for model predictive control by considering the timing as optimization constraints. This timing model allows multiple controllers to share a CAN without significant degradation in the controller performance. The timing model also provides a convenient way to check the schedulability of messages on the CAN at runtime. Simulation results demonstrate that the timing model is accurate and computationally efficient to meet the needs of real-time implementation. Simulation results also demonstrate that model predictive controllers designed when considering the timing constraints have superior performance than the controllers designed without considering the timing constraints.
机译:在共享控制器局域网(CAN)上实现多个模型预测控制器时,由于可变的时序和消息之间的延迟,其性能可能会下降。 CAN上基于优先级的消息实时调度会引入复杂的事件计时,尤其是在消息类型和数量在运行时发生变化时。本文介绍了一种新颖的混合计时模型,可以在有限的时间范围内对消息的计时进行运行时预测。通过将时序视为优化约束,可以使用用于模型预测控制的优化算法来设计控制器。该时序模型允许多个控制器共享一个CAN,而不会显着降低控制器性能。时序模型还提供了一种方便的方法,可以在运行时检查CAN上消息的可调度性。仿真结果表明,该时序模型准确,计算效率高,可以满足实时实现的需求。仿真结果还表明,考虑时序约束而设计的模型预测控制器比未考虑时序约束而设计的控制器具有更好的性能。

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