Implementation of Model Predictive Control on The Pitch Motion of Train Simulator Platform with Load Torque Uncertain

A. Ramelan, A. Syaichu-Rohman, Allen Kelana
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Abstract

This paper presents an analysis of the non-linearity of the torque load on the pitch platform movement of train simulator. Angle modelling of pitch available in many researches. However, for the changes of torque loads in the train simulator there has been no research that examines it. Then, this is one of the novelty we provided in this research. Beside that, we simulate Model Predictive Control (MPC) with a plant that contains non-linearity using simulation tool. In order to show the performance, we analyze its data and make a conclusion. As a Linear Quadratic Regulator (LQR), MPC produces an optimal control signal that can overcome constraints such as saturation. In MPC implementation, we determine the number of horizons (N), weighting Q and R based on the desired specifications.. The simulation results showed that the MPC design can handle non-linearity well. However, it is merely a simulation. We have not applied it to a actual plant yet.
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负载转矩不确定时列车模拟器平台俯仰运动模型预测控制的实现
本文分析了列车模拟器俯仰平台运动中扭矩载荷的非线性特性。俯仰的角度建模在许多研究中都有应用。然而,对于列车模拟器中转矩载荷的变化,目前还没有研究对其进行检验。这是我们在这项研究中提供的新奇之处之一。除此之外,我们还利用仿真工具对包含非线性的对象进行了模型预测控制(MPC)的仿真。为了展示其性能,我们对其数据进行了分析并得出结论。作为线性二次型调节器(LQR), MPC产生的最优控制信号可以克服诸如饱和等限制。在MPC实现中,我们根据期望的规格确定层数(N),加权Q和R。仿真结果表明,MPC设计能够很好地处理非线性。然而,这仅仅是一个模拟。我们还没有把它应用到实际的植物上。
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