从陆军面临的空中威胁目标出发,分析了陆军野战防空的主要特点及对指挥自动化系统的要求,提出了基于地理信息系统(Geographic Information System:GIS)的陆军野战防空指挥自动化系统的设想,并建立了基本的结构模型。最后,根据系统论的...从陆军面临的空中威胁目标出发,分析了陆军野战防空的主要特点及对指挥自动化系统的要求,提出了基于地理信息系统(Geographic Information System:GIS)的陆军野战防空指挥自动化系统的设想,并建立了基本的结构模型。最后,根据系统论的思想更深层地说明了陆军野战防空指挥自动化系统建设的重要性。展开更多
This paper considers the adaptive finite-time control and observer design method for a class of non-strict feedback systems with unmeasurable states,unknown nonlinear dynamics and actuator faults.In this paper,an obse...This paper considers the adaptive finite-time control and observer design method for a class of non-strict feedback systems with unmeasurable states,unknown nonlinear dynamics and actuator faults.In this paper,an observer is proposed to estimate the unmeasurable states in finite-time based on adaptive technique and neural networks,while the actuator faults are not included.Command filter is used to solve the computational explosion and singularity problems caused by the traditional backstepping and non-strict feedback structure,respectively.Since the fault efficiency indicators in real systems are not available,two-layer neural networks are adopted,where the first network is to estimate the unknown nonlinearities of systems and the second one is to estimate fault efficiency indicators and unknown nonlinear terms.The proposed scheme guarantees that states are bounded through stability theorem.Finally,two experiments including a numerical example and a spring-mass-damper system are given to verify the effectiveness of the proposed method.展开更多
In this paper, a command filter-based adaptive fuzzy predefined-time event-triggered tracking control problem is investigated for uncertain nonlinear systems with time-varying full-state constraints. By designing a sl...In this paper, a command filter-based adaptive fuzzy predefined-time event-triggered tracking control problem is investigated for uncertain nonlinear systems with time-varying full-state constraints. By designing a sliding mode differentiator, the inherent computational complexity problem within the predefined-time backstepping framework is solved. Different from the existing command filter-based finite-time and fixed-time control strategies that the convergence time of the filtering error is adjusted through the system initial value or numerous parameters, a novel command filtering error compensation method is presented,which tunes one control parameter to make the filtering error converge in the predefined time, thereby reducing the complexity of design and analysis of processing the filtering error. Then, an improved event-triggered mechanism(ETM) that builds upon the switching threshold strategy, in which an inverse cotangent function is designed to replace the residual term of the ETM,is proposed to gradually release the controller's dependence on the residual term with increasing time. Furthermore, a tan-type nonlinear mapping technique is applied to tackle the time-varying full-state constraints problem. By the predefined-time stability theory, all signals in the uncertain nonlinear systems exhibit predefined-time stability. Finally, the feasibility of the proposed algorithm is substantiated through two simulation results.展开更多
文摘从陆军面临的空中威胁目标出发,分析了陆军野战防空的主要特点及对指挥自动化系统的要求,提出了基于地理信息系统(Geographic Information System:GIS)的陆军野战防空指挥自动化系统的设想,并建立了基本的结构模型。最后,根据系统论的思想更深层地说明了陆军野战防空指挥自动化系统建设的重要性。
基金supported by the National Natural Science Foundation of China under Grant Nos.62003183,62373208,and 62003097the Taishan Scholar program of Shandong Province of China under Grant No.tsqn202306218the Talent Introduction and Cultivation Plan for Youth Innovation of Universities in Shandong Province。
文摘This paper considers the adaptive finite-time control and observer design method for a class of non-strict feedback systems with unmeasurable states,unknown nonlinear dynamics and actuator faults.In this paper,an observer is proposed to estimate the unmeasurable states in finite-time based on adaptive technique and neural networks,while the actuator faults are not included.Command filter is used to solve the computational explosion and singularity problems caused by the traditional backstepping and non-strict feedback structure,respectively.Since the fault efficiency indicators in real systems are not available,two-layer neural networks are adopted,where the first network is to estimate the unknown nonlinearities of systems and the second one is to estimate fault efficiency indicators and unknown nonlinear terms.The proposed scheme guarantees that states are bounded through stability theorem.Finally,two experiments including a numerical example and a spring-mass-damper system are given to verify the effectiveness of the proposed method.
基金supported by the Revitalization of Liaoning Talents Program(Grant No.XLYC2203201)。
文摘In this paper, a command filter-based adaptive fuzzy predefined-time event-triggered tracking control problem is investigated for uncertain nonlinear systems with time-varying full-state constraints. By designing a sliding mode differentiator, the inherent computational complexity problem within the predefined-time backstepping framework is solved. Different from the existing command filter-based finite-time and fixed-time control strategies that the convergence time of the filtering error is adjusted through the system initial value or numerous parameters, a novel command filtering error compensation method is presented,which tunes one control parameter to make the filtering error converge in the predefined time, thereby reducing the complexity of design and analysis of processing the filtering error. Then, an improved event-triggered mechanism(ETM) that builds upon the switching threshold strategy, in which an inverse cotangent function is designed to replace the residual term of the ETM,is proposed to gradually release the controller's dependence on the residual term with increasing time. Furthermore, a tan-type nonlinear mapping technique is applied to tackle the time-varying full-state constraints problem. By the predefined-time stability theory, all signals in the uncertain nonlinear systems exhibit predefined-time stability. Finally, the feasibility of the proposed algorithm is substantiated through two simulation results.
