Qi Wenhai, Zhang Ning, Zong Guangdeng, Su Shun-Feng, Yan Huaicheng, Yeh Ruey-Huei
IEEE Trans Cybern. 2023 Oct;53(10):6503-6515. doi: 10.1109/TCYB.2023.3253701. Epub 2023 Sep 15.
The event-triggered sliding-mode control (SMC) for discrete-time networked Markov jumping systems (MJSs) with channel fading is investigated by means of a genetic algorithm. In order to reduce resource consumption in the transmission process, an event-triggered protocol is adopted for networked MJSs. A key feature is that the signal transmission is inevitably affected by fading phenomenon due to delay, random noise, and amplitude attenuation in a networked environment. With the aid of a common sliding surface, an event-triggered SMC law is designed by adjusting the system network mode. Under the framework of stochastic Lyapunov stability, sufficient conditions are constructed to ensure the mean-square stability of the closed-loop networked MJSs, and the sliding region is reached around the specified sliding surface. Moreover, based on the iteration optimizing accessibility of objective function, an effective SMC approach under genetic algorithm is proposed to minimize the convergence region around the sliding surface. Finally, the effectiveness of the proposed method is proved by the F-404 aircraft model.
利用遗传算法研究了具有信道衰落的离散时间网络化马尔可夫跳跃系统（MJS）的事件触发滑模控制（SMC）。为了减少传输过程中的资源消耗，对网络化MJS采用了事件触发协议。一个关键特性是，在网络环境中，由于延迟、随机噪声和幅度衰减，信号传输不可避免地受到衰落现象的影响。借助一个通用滑模面，通过调整系统网络模式设计了一种事件触发SMC律。在随机李雅普诺夫稳定性框架下，构建了充分条件以确保闭环网络化MJS的均方稳定性，并在指定滑模面周围到达滑模区域。此外，基于目标函数迭代优化可达性，提出了一种遗传算法下的有效SMC方法，以最小化滑模面周围的收敛区域。最后，通过F - 404飞机模型验证了所提方法的有效性。
