Output Feedback Model Predictive Control for Interval Type-2 T-S Fuzzy Networked Control Systems
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摘要: 针对干扰作用下的非线性网络控制系统,给出了带一个自由控制作用的输出反馈预测控制方法.首先,利用区间二型T-S模糊模型描述具有参数不确定性的非线性对象,采用马尔科夫链描述系统中的随机丢包过程,由此建立了丢包网络环境下的非线性网络控制系统的数学模型.然后,通过引入二次有界技术得到了干扰作用下网络控制系统的稳定性描述方法,并在此基础上给出了状态观测器的线性矩阵不等式条件.最后,基于估计状态,通过将无穷时域控制作用参数化为一个自由控制作用加一个线性反馈律得到了输出反馈预测控制方法.论文的特色在于构建了在线更新误差椭圆集合的基本方法,满足了约束条件下输出反馈预测控制保证稳定性的要求.仿真例子验证了所提方法的有效性.Abstract: For non-linear networked control systems with bounded disturbances, this paper presents an output feedback predictive control approach with one free control move. Firstly, an interval type-2 T-S fuzzy model is employed to describe the non-linear plant which is subject to parameter uncertainties, and a Markov chain is introduced to characterize the process of stochastic packet loss of the system, thus a mathematical model of non-linear networked control system with packet loss is established. Then, a method of describing the stability for a networked control system with bounded disturbances is obtained by using the technique of quadratic boundedness. With the help of the provided method, the linear matrix inequality conditions of the state observer are given. Finally, based on the estimated state, an output feedback predictive control algorithm is developed which parameterizes the infinite horizon control moves into one free control move and a linear feedback law. The main feature of this paper is that an essential formula for on-line refreshing ellipsoidal bounds of estimation errors is introduced, which meets the requirement of guaranteeing the stability of output feedback predictive control with input constraints. An example is given to demonstrate the effectiveness of the proposed method.
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Key words:
- Networked control systems /
- predictive control /
- interval type-2 /
- quadratic boundedness
1) 本文责任编委 刘艳军 -
表 1 观测器参数, 性能指标及计算时间
Table 1 Observer parameters, performance objective, and computational time
H0 Lp $J_0^\infty $ TAverage $\left[ \begin{array}{l} 0.7833\;\;\;0.0643\\ 0.0643\;\;\;1.0316 \end{array} \right] $ $\left[ \begin{array}{l} 0.0018\\ 0.5394 \end{array} \right] $ 62.98 0.93 s -
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