This article presents a novel finite-time adaptive fuzzy event-triggered control strategy for stochastic nonlinear systems in nonstrict feedback structure, where time-varying output constraints ...(TVOC) and input delay are considered. To deal with the output constraints, a stochastic nonlinear mapping is developed to transform the original system into an equivalent one without output constraints. Furthermore, the Pade approximation method is applied to address the input delay by introducing a new intermediate variable. Then, a novel adaptive event-triggered mechanism is proposed to reduce the number of data transmissions and mitigate the effects of tracking error. The stability analysis shows that the closed-loop signals are semiglobal finite-time stable in probability (SGFSP), while the tracking performances are well and satisfy the output constraint condition. Finally, simulation results are to demonstrate the effectiveness of the developed approach.
This paper proposes an enhanced chaos synchronization control scheme of stochastic nonlinear systems for the permanent magnet synchronous motors(PMSMs) applications for dynamic operating mechanism ...under different working environment. Firstly, a novel fixed-time stochastic stability theorem and convergence for the stochastic nonlinear system is valid through formulating a novel Lyapunov function. Different from what has been achieved on the fixed-time stability, it’s not the usual range but it’s more precise for settling time which improving control performance effectually. Secondly, the chaos synchronization issue of driven-response PMSMs with stochastic noise is firstly investigated based on the proposed Lyapunov theorem synchronizing the complex dynamic systems considering practical significance. Finally, the fixed-time synchronization control scheme is developed via applying the adaptive algorithms, furthermore, through constructing a reasonable synchronization dynamic error system achieving stability in probability of fixed time. A simulation analysis is demonstrated to verify the availability of the proposed control strategy.
This paper investigates the situation awareness issue of power system with massive measured data. To address this issue, first, a graph-theory-based network partitioning algorithm is proposed to ...realize decentralized detection in a faster response speed, while using power flow characteristics highlights the independency of different groups. Further, a hierarchical event detection method is proposed to judge voltage change and locate event position according to spectral distribution change of established multidimensional matrix. With the proposed method, the system situation can be assessed and the knowledge of the system model is not required. In addition, the accurate result of weak event happened in system could also be obtained. The simulation results are presented to illustrate the effectiveness of the proposed detection method.
This article proposed a novel event-triggered integral sliding-mode control (ISMC) strategy for nonlinear system with disturbances via robust adaptive dynamic programming (ADP) considering control ...constrains. A mixed event-triggered ISMC scheme with two different trigger parts is developed and the optimal performance of sliding-mode dynamics with input constrains is ensured. By guaranteeing that the system trajectory converges to the sliding-mode surface with removing the input disturbances, a discontinuous part triggering rule is presented together with the existence analysis of a lower trigger interval time bound. Then, the optimal event-triggered control of sliding-mode dynamics is converted into a discounted factor-based <inline-formula> <tex-math notation="LaTeX">H_{\infty } </tex-math></inline-formula> constrained control problem under continuous part triggering condition. To solve the event-triggered HJI equation, a critic-only neural network (NN)-based ADP scheme is developed by applying a concurrent learning. The NN weight is updated by analyzing the uniformly ultimately bounded (UUB) stability of sliding-mode dynamics considering the event-triggered condition via the Lyapunov technique. Finally, the validity of our control strategy is verified by simulation.
•A novel finite-time DFEO is designed to estimate more general faults in all subsystems of CPSs based on the distributed functional observer with an adaptive compensator. Not only the order and ...complexity of observer are reduced, but also the unknown parameters of matched uncertainties are adaptively learned to improve the convergence and precision of observer. Both the transient performance in finite time and H∞ disturbance attenuate performance of CPSs are achieved.•A DFTCr based on the integral SMC is designed to compensate the effect of faults on the interconnected CPSs, in which the sliding surface function does not include the system parameters, which makes the design more flexible. Moreover, compared with the existing research 23, 28, the controller in this paper does not need to give the limited assumption of pseudo inverse.•The FTB-H∞ performance with nonzero initial conditions of CPSs is ensured by employing a new Lyapunov functional approach. Compared with the matched nonlinear function with known upper bounded conditions in 29, and measurable states 32, our works are more general and practical.
This paper is concerned with finite-time distributed fault estimation (DFE) and fault-tolerant control (DFTC) for cyber-physical systems (CPSs) with actuator faults and matched uncertainties. First, in order to deal with the partly unmeasurable states, matched uncertainties and actuator faults with the loss of effectiveness and bias, a distributed fault estimation observer (DFEO) is designed based on the functional observer with an adaptive compensator. Then, a distributed fault-tolerant controller (DFTCr) is designed to compensate faults effect on the interconnected CPSs based on the integral sliding mode control (SMC) technique, which ensures that the closed-loop systems reach a given boundedness in a predefined finite time. Moreover, some sufficient conditions in the form of linear matrix inequalities are proposed to guarantee the finite-time boundedness with H∞ performance (FTB-H∞). Due to introducing more degrees of freedom of the functional observer, the designed finite-time distributed fault-tolerant controller is more flexible and less conservative. Finally, a numerical simulation on the three-machine power systems is acquired to show the validity of the proposed method.
This letter presents an adaptive synchronization scheme between two different kinds of delayed chaotic neural networks (NNs) with partly unknown parameters. An adaptive controller is designed to ...guarantee the global asymptotic synchronization of state trajectories for two different chaotic NNs with time delay. An illustrative example is given to demonstrate the effectiveness of the present method.
This article focuses on the distributed robust fault estimation problem for a kind of discrete-time interconnected systems with input and output disturbances. For each subsystem, by letting the fault ...as a special state, an augmented system is constructed. Particularly, the dimensions of system matrices after augmentation are lower than some existing related results, which may help to reduce calculation amount, especially, for linear matrix inequality-based conditions. Then, a distributed fault estimation observer design scheme that utilizes the associated information among subsystems is presented to not only reconstruct faults, but also suppress disturbances in the sense of robust <inline-formula> <tex-math notation="LaTeX">H_{\infty}</tex-math> </inline-formula> optimization. Besides, to improve the fault estimation performance, a common Lyapunov matrix-based multiconstrained design method is first given to solve the observer gain, which is further extended to the different Lyapunov matrices-based multiconstrained calculation method. Thus, the conservatism is reduced. Finally, simulation experiments are shown to verify the validity of our distributed fault estimation scheme.
Idiopathic congenital nystagmus (CN) is a rare eye disease that can cause early blindness (EB). CN deficits are observed most frequently with oculomotor dysfunction; however, it is still unclear what ...neuromechanics underly CN with EB. Based on that visual experience requires the functional integration of both hemispheres, we hypothesized that CN adolescents with EB might exhibit impaired interhemispheric synchrony. Our study aimed to investigate the interhemispheric functional connectivity alterations using voxel-mirrored homotopic connectivity (VMHC) and their relationships with clinical features in CN patients.
This study included 21 patients with CN and EB, and 21 sighted controls (SC), who were matched for sex, age and educational level. The 3.0 T MRI scan and ocular examination were performed. The VMHC differences were examined between the two groups, and the relationships between mean VMHC values in altered brain regions and clinical variables in the CN group were evaluated by Pearson correlation analysis.
Compared with the SC group, the CN had increased VMHC values in the bilateral cerebellum posterior and anterior lobes/cerebellar tonsil/declive/pyramis/culmen/pons, middle frontal gyri (BA 10) and frontal eye field/superior frontal gyri (BA 6 and BA 8). No particular areas of the brain had lower VMHC values. Furthermore, no correlation with the duration of disease or blindness could be demonstrated in CN.
Our results suggest the existence of interhemispheric connectivity changes and provide further evidence for the neurological basis of CN with EB.
As a core component of the biomass, the important role of extracellular polymeric substances (EPS) on treatment performance has been recognized. However, the comprehensive understanding of its ...correlation with nitrogen removal remains limited in biofilm-based reactors. In this study, the relevance between EPS and advanced nitrogen removal in a novel step-feed three-stage integrated anoxic/oxic biofilter (SFTIAOB) was specifically investigated. The operation showed as high as 81% TN removal was achieved under optimal conditions. Among the whole reactor, 2nd anoxic (A2) zone was the largest contributor for nitrogen removal, followed by the 3rd anoxic (A3) and 2nd oxic (O2) zones. EPS composition analysis found that high content of polysaccharides in tightly bound-EPS (A2 and A3) and protein in loosely bound-EPS and tightly bound-EPS (O2). Fourier transform infrared spectroscopy, three-dimensional fluorescence spectrum further verified stratified EPS subfractions containing different secondary protein structures, while 3-turn helix and tryptophan-like protein was the main reason for nitrogen removal. High-throughput sequencing revealed the co-existence of nitrogen removal-associated genera accomplished nitrification/denitrification combined with aerobic denitrification and anammox. Moreover, the correlation of EPS and microbial composition with nitrogen removal was clarified by redundancy analysis (RDA). Finally, potential mechanism for nitrogen removal was illuminated. This research gives more insight into EPS characteristics in enhancing nitrogen removal during the operation and optimization of a step-feed multi-stage A/O biofilm process.
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•Nitrogen removal and EPS analysis of the whole SFTIAOB system were investigated.•High PS in TB-EPS (A2 and A3) and PN in LB-EPS and TB-EPS (O2) were found.•Abundant 3-turn helix and tryptophan-like protein promoted nitrogen removal.•Correlation of EPS and microbial composition with nitrogen removal was revealed.•Potential mechanism for advanced nitrogen removal was illuminated.
The intermittency of renewable energy and the uncertainty of load put forward higher robustness requirements for the frequency recovery of microgrid (MG). The energy storage equipment provides an ...idea for frequency control because of its fast response and strong controllability. In this paper, an on-line adaptive frequency control method is proposed to control the governor and energy storage to realize the frequency recovery of MG under stochastic uncertainty. First, the MG system with external disturbances is constructed as a zero-sum differential game model to obtain a robust optimal control scheme. Then, considering the system parameter uncertainty, an improved integral reinforcement learning (IRL) algorithm is designed, in which the reinforcement signal contains a non-quadratic function to solve the energy storage control constraints. Furthermore, a novel dynamic event-triggered control (DETC) is developed to reduce control update times of energy storage. The dynamic variable in DETC coupled with static trigger includes not only the past triggering information but also the disturbances. DETC has a larger trigger threshold than static event-triggered control (SETC). Meanwhile, the proposed algorithm is implemented by an action-critic network structure, in which the action network of energy storage is updated aperiodically. Finally, simulation results show that the proposed control algorithm can realize the frequency recovery of MG, and it has good robustness compared with other algorithms.
