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Hybrid multi-parametric model predictive control of a nonlinear process approximated with a piecewise affine model

机译:用分段仿射模型近似的非线性过程的混合多参数模型预测控制

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摘要

The recently developed methods of multi-parametric model predictive control (mp-MPC) for hybrid systems provide an interesting opportunity for solving a class of nonlinear control problems. With this approach, the nonlinear process is approximated by a piecewise affine (PWA) hybrid model, containing a set of local linear dynamics. Compared to linear model based MPC, a performance improvement is expected with the reduction of plant-to-model mismatch. The feasibility of the approach for application was evaluated in a case study, where an output feedback, offset-free tracking hybrid mp-MPC controller was considered as a replacement for a PID controller based scheme for control of pressure in a wire annealing machine. The evaluation was carried out on a nonlinear model of the process.
机译:最近开发的用于混合系统的多参数模型预测控制(mp-MPC)方法为解决一类非线性控制问题提供了有趣的机会。使用这种方法,可以通过分段仿射(PWA)混合模型来近似非线性过程,该模型包含一组局部线性动力学。与基于线性模型的MPC相比,通过减少工厂与模型之间的不匹配,有望提高性能。在案例研究中评估了该方法的可行性,在该案例研究中,将输出反馈,无偏移跟踪混合mp-MPC控制器视为基于PID控制器的线材退火机压力控制方案的替代品。评估是在过程的非线性模型上进行的。

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