In this work, we consider economic model predictive control of nonlinear networked control systems subject to external disturbances and communication delays in both sensor‐to‐controller and controller‐to‐actuator channels. The problem is addressed in the framework of the min‐max model predictive control. First, a delay compensation strategy is proposed to minimize the impact of communication delays on the control performance. In the compensation strategy, once the receiver at the controller node receives a new state measurement, the controller generates a control sequence and sends the sequence to the actuator to compensate for delayed control inputs. Subsequently, the presence of disturbance is explicitly considered for robustness and the semi‐feedback min‐max optimization algorithm is used to design the control law based on the estimate of the current state reconstructed by the estimator. Furthermore, the input‐to‐state practical stability of the proposed approach is established by constructing a modified Lyapunov function. Simulation results of a numerical example and a chemical process example demonstrate the applicability and effectiveness of our approach.

中文翻译：

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具有通信延迟的非线性网络控制系统的鲁棒经济模型预测控制

在这项工作中，我们考虑非线性网络控制系统的经济模型预测控制，该系统在传感器到控制器和控制器到执行器的通道中都受到外部干扰和通信延迟的影响。在最小-最大模型预测控制的框架中解决了该问题。首先，提出了一种延迟补偿策略，以最大程度地减少通信延迟对控制性能的影响。在补偿策略中，一旦控制器节点上的接收器接收到新的状态测量值，控制器就会生成控制序列，并将该序列发送给执行器以补偿延迟的控制输入。后来，明确考虑了扰动的存在以提高鲁棒性，并且基于估计器重构的当前状态的估计，使用半反馈最小最大值优化算法来设计控制律。此外，通过构造改进的Lyapunov函数，可以建立所提出方法的输入状态实用稳定性。数值实例和化学过程实例的仿真结果证明了我们方法的适用性和有效性。