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Robust model predictive control for discrete uncertain nonlinear systems with time-delay via fuzzy model

机译:不确定时滞非线性不确定系统的鲁棒模型预测控制

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摘要

An extended robust model predictive control approach for input constrained discrete uncertain nonlinear systems with time-delay based on a class of uncertain T-S fuzzy models that satisfy sector bound condition is presented. In this approach, the minimization problem of the "worst-case" objective function is converted into the linear objective minimization problem involving linear matrix inequalities (LMIs) constraints. The state feedback control law is obtained by solving convex optimization of a set of LMIs. Sufficient condition for stability and a new upper bound on robust performance index are given for these kinds of uncertain fuzzy systems with state time-delay. Simulation results of CSTR process show that the proposed robust predictive control approach is effective and feasible.
机译:提出了基于一类满足扇区界条件的不确定T-S模糊模型的输入受限时滞离散不确定非线性系统的扩展鲁棒模型预测控制方法。在这种方法中,将“最坏情况”目标函数的最小化问题转换为涉及线性矩阵不等式(LMI)约束的线性目标最小化问题。通过求解一组LMI的凸优化来获得状态反馈控制律。针对这类具有状态时滞的不确定模糊系统,给出了充分的稳定性条件和鲁棒性能指标的新上限。 CSTR过程的仿真结果表明,所提出的鲁棒预测控制方法是有效可行的。

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