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Model Predictive Control of a Highly Nonlinear Process Based on Piecewise Linear Wiener Models

机译:基于分段线性维纳模型的高度非线性过程的模型预测控制

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In this paper a nonlinear model predictive control (NMPC) based on a piecewise linear wiener model is presented. The nonlinear gain of this particular wiener model is approximated using the piecewise linear functions. This approach retains all the interested properties of the classical linear model predictive control (MPC) and keeps computations easy to solve due to the canonical structure of the nonlinear gain. The presented control scheme is applied to a pH neutralization process and simulation results are compared to linear model predictive control. Simulation results show that the nonlinear controller has better performance without any overshoot in comparison with linear MPC and also less steady-state error in tracking the set -points.
机译:本文提出了一种基于分段线性维纳模型的非线性模型预测控制(NMPC)。使用分段线性函数近似该特定维纳模型的非线性增益。这种方法保留了经典线性模型预测控制(MPC)的所有感兴趣的特性,并且由于非线性增益的规范结构,保持易于解决的计算。将呈现的控制方案应用于pH中和过程,并将仿真结果与线性模型预测控制进行比较。仿真结果表明,与线性MPC相比,非线性控制器具有更好的性能而没有任何过冲,并且在跟踪设定点时也较低的稳态误差。

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