The paper presents an adaptive controller formulated for a class of nonaffine discrete-time systems with non-strict forms and unknown dynamics.The controller operates based solely on the measured output,thus obviating...The paper presents an adaptive controller formulated for a class of nonaffine discrete-time systems with non-strict forms and unknown dynamics.The controller operates based solely on the measured output,thus obviating the need for knowledge of the physical order of the controlled plant.Utilizing an ideal solution and equivalent dynamics,the approach integrates an adaptive network with feedback and robust controllers to establish a closed-loop system.A learning law is derived under practical conditions of the designed parameters,ensuring effective closed-loop performance based on pure-output feedback.The controller’s effectiveness is validated through both numerical and experimental systems,with results meeting the conditions specified in the main theorem.Comparative analysis highlights the controller’s highly satisfactory performance and its advantages.This research offers a promising approach to adaptive control for discrete-time systems with non-strict dynamics,providing practical solutions for systems with unknown dynamics and indeterminate system order.展开更多
This paper considers the leader-following consensus for a class of nonlinear switched multi-agent systems(MASs)with non-strict feedback forms and input saturations under unknown switching mechanisms.First,in virtue of...This paper considers the leader-following consensus for a class of nonlinear switched multi-agent systems(MASs)with non-strict feedback forms and input saturations under unknown switching mechanisms.First,in virtue of Gaussian error functions,the saturation nonlinearities are represented by asymmetric saturation models.Second,neural networks are utilized to approximate some unknown packaged functions,and the structural property of Gaussian basis functions is introduced to handle the non-strict feedback terms.Third,by using the backstepping process,a common Lyapunov function is constructed for all the subsystems of the followers.At last,we propose an adaptive consensus protocol,under which the tracking error under arbitrary switching converges to a small neighborhood of the origin.The effectiveness of the proposed protocol is illustrated by a simulation example.展开更多
In this paper we use the notion of measure of non-strict-singularity to give some results on Fredholm operators and we establish a fine description of the Schechter essential spectrum of a closed densely defined linea...In this paper we use the notion of measure of non-strict-singularity to give some results on Fredholm operators and we establish a fine description of the Schechter essential spectrum of a closed densely defined linear operator.展开更多
In this article,the problem of event-triggered adaptive fuzzy finite time control of nonstrict feedback fractional order nonlinear systems is investigated.By using the property of fuzzy basis function,the obstacle cau...In this article,the problem of event-triggered adaptive fuzzy finite time control of nonstrict feedback fractional order nonlinear systems is investigated.By using the property of fuzzy basis function,the obstacle caused by algebraic loop problems is successfully circumvented.Moreover,a new adaptive event-triggered scheme is designed under the unified framework of backstepping control method,which can largely reduce the amount of communications.The stability of the closed-loop system is ensured through fractional Lyapunov stability analysis.Finally,the effectiveness of the proposed scheme is verified by simulation examples.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
文摘The paper presents an adaptive controller formulated for a class of nonaffine discrete-time systems with non-strict forms and unknown dynamics.The controller operates based solely on the measured output,thus obviating the need for knowledge of the physical order of the controlled plant.Utilizing an ideal solution and equivalent dynamics,the approach integrates an adaptive network with feedback and robust controllers to establish a closed-loop system.A learning law is derived under practical conditions of the designed parameters,ensuring effective closed-loop performance based on pure-output feedback.The controller’s effectiveness is validated through both numerical and experimental systems,with results meeting the conditions specified in the main theorem.Comparative analysis highlights the controller’s highly satisfactory performance and its advantages.This research offers a promising approach to adaptive control for discrete-time systems with non-strict dynamics,providing practical solutions for systems with unknown dynamics and indeterminate system order.
基金supported in part by the National Key Research and Development Program(2018YFA0702202)in part by the Leadingedge Technology Program of Jiangsu National Science Foundation(BK20202011)in part by the Research Grants of the Nanjing University of Posts and Telecommunications(NY220158,NY220177)。
文摘This paper considers the leader-following consensus for a class of nonlinear switched multi-agent systems(MASs)with non-strict feedback forms and input saturations under unknown switching mechanisms.First,in virtue of Gaussian error functions,the saturation nonlinearities are represented by asymmetric saturation models.Second,neural networks are utilized to approximate some unknown packaged functions,and the structural property of Gaussian basis functions is introduced to handle the non-strict feedback terms.Third,by using the backstepping process,a common Lyapunov function is constructed for all the subsystems of the followers.At last,we propose an adaptive consensus protocol,under which the tracking error under arbitrary switching converges to a small neighborhood of the origin.The effectiveness of the proposed protocol is illustrated by a simulation example.
文摘In this paper we use the notion of measure of non-strict-singularity to give some results on Fredholm operators and we establish a fine description of the Schechter essential spectrum of a closed densely defined linear operator.
基金the Funds of National Science of China under Grant Nos.61973146 and 61773188in part by the Distinguished Young Scientific Research Talents Plan in Liaoning Province under Grant Nos.XLYC1907077 and JQL201915402。
文摘In this article,the problem of event-triggered adaptive fuzzy finite time control of nonstrict feedback fractional order nonlinear systems is investigated.By using the property of fuzzy basis function,the obstacle caused by algebraic loop problems is successfully circumvented.Moreover,a new adaptive event-triggered scheme is designed under the unified framework of backstepping control method,which can largely reduce the amount of communications.The stability of the closed-loop system is ensured through fractional Lyapunov stability analysis.Finally,the effectiveness of the proposed scheme is verified by simulation examples.
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.
