耗散系统                        
                
                                
                        
                            执行机构                        
                
                                
                        
                            控制理论(社会学)                        
                
                                
                        
                            概率逻辑                        
                
                                
                        
                            控制器(灌溉)                        
                
                                
                        
                            计算机科学                        
                
                                
                        
                            伯努利分布                        
                
                                
                        
                            外稃(植物学)                        
                
                                
                        
                            随机变量                        
                
                                
                        
                            控制(管理)                        
                
                                
                        
                            数学                        
                
                                
                        
                            物理                        
                
                                
                        
                            生物                        
                
                                
                        
                            人工智能                        
                
                                
                        
                            统计                        
                
                                
                        
                            农学                        
                
                                
                        
                            量子力学                        
                
                                
                        
                            禾本科                        
                
                                
                        
                            生态学                        
                
                        
                    
            作者
            
                Haiyang Chen,Guangdeng Zong,Fangzheng Gao,Yang Shi            
         
                    
        
    
            
            标识
            
                                    DOI:10.1109/tac.2023.3246429
                                    
                                
                                 
         
        
                
            摘要
            
            This technical note investigates the problem of extended dissipative finite-time control for Markov jump systems (MJSs) with cyber-attacks and actuator failures. A probabilistic event-triggered mechanism (PETM) is proposed to relieve the communication burden by exploiting both the pattern variation of triggering thresholds and the time-varying characteristic of transmission delays. To characterize the actual control inputs, a stochastic actuator failure model (SAFM) is established using a random variable of any discrete-time distribution over [0, 1]. First, based on the PETM and SAFM, static output-feedback controllers are devised, which may not switch with the system synchronously. Then, novel sufficient conditions with less conservatism are obtained to achieve the extended dissipative finite-time control performance of the closed-loop system under admissible cyber-attacks and actuator failures. Furthermore, controller gains with nonconvex constraints are calculated with the aid of a newly proposed lemma. Finally, an application oriented example is provided to verify the effectiveness and superiority of the proposed results.
         
            
 
                 
                
                    
                    科研通智能强力驱动
Strongly Powered by AbleSci AI