In this paper, the periodic tracking control problem is considered for nonlinear systems with some parameters uncertainties and disturbances. First, a T-S fuzzy approach is employed to model ...nonlinear systems. Second, considering the partly state unmeasured and periodic tracking reference signal, fuzzy state observer and fuzzy modified repetitive controller (FMRCr) are designed based on the modified repetitive control (MRC) approach. To achieve signal tracking and H∞ disturbance attenuation performance, a two-dimensional model approach and singular-value decomposition technique of system output matrix are developed. Then, by the Lyapunov stability theory, some sufficient conditions are obtained for FMRC closed-loop system with stabilization and H∞ disturbance attenuation performance in linear matrix inequality (LMI) form. Correspondingly, the controller gains and observer gains are solved by LMI toolbox. Two numerical examples are provided to illustrate the validity of the method.
Inorganic particles with photocatalytic properties are excellent candidates for the fabrication of micromotors. To achieve self-propulsion, the geometric and chemical symmetries of inorganic ...particles should be broken. However, the synthesis of micromotors with different geometric and chemical symmetries remains challenging. In this paper, a simple synthesis method is proposed to prepare rod-shaped micromotors with different patches, leading to distinct geometric and chemical symmetries. The micromotors are composed of zinc oxide (ZnO) microrods partially patched with polysiloxanes at different positions. The patches of the micromotors can be roughly regulated by varying the amount of siloxanes used in the synthesis. These micromotors are propelled in H2O2 solution by an ionic self-diffusiophoresis mechanism, which exhibits two motion modes, including linear motion and circular motion, due to different patch positions. Moreover, the degradation of organic dyes by the micromotors depending on the patches is demonstrated.
Congenital nystagmus in infants and young children can lead to early blindness (EB). Previous neuroimaging studies have demonstrated that EB is accompanied by alterations in brain structure and ...function. However, the effects of visual impairment and critical developmental periods on brain functional connectivity at rest have been unclear. Here, we used the voxel-wise degree centrality (DC) method to explore the underlying functional network brain activity in adolescents with EB. Twenty-one patients with EBs and 21 sighted controls (SCs) underwent magnetic resonance imaging. Differences between the two groups were assessed using the DC method. Moreover, the support vector machine (SVM) method was used to differentiate patients with EB patients from the SCs according to DC values. Compared with the SCs, the patients with EB had increased DC values in the bilateral cerebellum_6, cerebellum vermis_4_5, bilateral supplementary motor areas (SMA), and left fusiform gyrus; the patients with EB had decreased DC values in the bilateral rectal gyrus and left medial orbital frontal gyrus. The SVM classification of the DC values achieved an overall accuracy of 70.45% and an area under the curve of 0.86 in distinguishing between the patients with EB and the SCs. Our study may reveal the neuromechanism of neuroplasticity in EB; the findings provide an imaging basis for future development of restorative visual therapies and sensory substitution devices, and future assessments of visual rehabilitation efficacy.
Adaptive dynamic programming (ADP), an important branch of reinforcement learning, is a powerful tool in solving various optimal control problems. However, the cooperative game issues of ...discrete-time multi-player systems with control constraints have rarely been investigated in this field. In order to address this issue, a novel policy iteration (PI) algorithm is proposed based on ADP technique, and its associated convergence analysis is also studied in this brief paper. For the proposed PI algorithm, an online neural network (NN) implementation scheme with multiple-network structure is presented. In the online NN-based learning algorithm, critic network, constrained actor networks and unconstrained actor networks are employed to approximate the value function, constrained and unconstrained control policies, respectively, and the NN weight updating laws are designed based on the gradient descent method. Finally, a numerical simulation example is illustrated to show the effectiveness.
The microgrid with the high proportion of renewable sources has become the trend of the future. However, the negative features, such as renewable energy perturbation, nonlinear counterpart, and so ...on, are prone to causing the low-power quality of the ac microgrid. To deal with these problems, this article proposes an event-triggered consensus control approach. First, the nonlinear state-space function regarding the ac microgrid is built, which is further transformed into the standard linear multiagent model by using the singular perturbation method. It provides indispensable preprocessing for the direct application of advanced linear control approaches. Then, based on this standard linear multiagent model, the secondary consensus approach with the leader is designed to compensate for the output voltage deviation and achieve accurate power sharing. In order to decrease the communication among various distributed generators, the event-triggered communication method is further proposed. Meanwhile, the Zeno behavior is avoided through the theoretical proof. Finally, simulation results are presented to demonstrate the effectiveness of the proposed approach.
In traditional leak location methods, the position of the leak point is located through the time difference of pressure change points of both ends of the pipeline. The inaccurate estimation of ...pressure change points leads to the wrong leak location result. To address it, adaptive dynamic programming is proposed to solve the pipeline leak location problem in this article. First, a pipeline model is proposed to describe the pressure change along pipeline, which is utilized to reflect the iterative situation of the logarithmic form of pressure change. Then, under the Bellman optimality principle, a value iteration (VI) scheme is proposed to provide the optimal sequence of the nominal parameter and obtain the pipeline leak point. Furthermore, neural networks are built as the VI scheme structure to ensure the iterative performance of the proposed method. By transforming into the dynamic optimization problem, the proposed method adopts the estimation of the logarithmic form of pressure changes of both ends of the pipeline to locate the leak point, which avoids the wrong results caused by unclear pressure change points. Thus, it could be applied for real-time leak location of long-distance pipeline. Finally, the experiment cases are given to illustrate the effectiveness of the proposed method.
Industrial cyber–physical systems generally suffer from the malicious attacks and unmatched perturbation, and thus the security issue is always the core research topic in the related fields. This ...paper proposes a novel intelligent secure control scheme, which integrates optimal control theory, zero-sum game theory, reinforcement learning and neural networks. First, the secure control problem of the compromised system is converted into the zero-sum game issue of the nominal auxiliary system, and then both policy-iteration-based and value-iteration-based adaptive dynamic programming methods are introduced to solve the Hamilton–Jacobi–Isaacs equations. The proposed secure control scheme can mitigate the effects of actuator attacks and unmatched perturbation, and stabilize the compromised cyber–physical systems by tuning the system performance parameters, which is proved through the Lyapunov stability theory. Finally, the proposed approach is applied to the Quanser helicopter to verify the effectiveness.
•Secure control problems are converted into zero-sum game issues.•Two mainstream ADP methods are introduced to solve HJI equations.•Tuning conditions of secure control parameters are derived.•The proposed control scheme is tested on the Quanser helicopter.
Extensive presence of aromatic organic compounds (AOCs) is a major course for the non-biodegradability of coking wastewater (COW). In-depth understanding of bio-degradation of AOCs is crucial for ...optimizing the design and operation of COW biological treatment systems in practical applications. Herein, the behavior and fate of AOCs were explored in a lab-scale step-feed three-stage integrated A/O biofilter (SFTIAOB) treating synthetic COW. Long-term operation demonstrated that COD, phenol, indole, quinoline and pyridine could be simultaneously removed. Phenol and indole were chiefly removed by anoxic zones, while quinoline and pyridine removal occurred in both anoxic and aerobic zones. Ultraviolet–visible spectrum observed that initial carboxylation and subsequent ring cracking and mineralization. Infrared spectroscopy also confirmed that key functional groups were cracked and produced during AOCs bio-degradation. Three-dimensional fluorescence spectrum indicated that significant transformation and elimination of tryptophan and humic acid with high molecular weight. Ring cleavage, distinct degradation and even complete mineralization of complex AOCs were further verified by gas chromatography-mass spectrometry. Moreover, functional degrading bacteria and aromatic ring-cleavage enzymes was successfully identified. Finally, AOCs biodegradation mechanisms by alternating anoxic and aerobic treatment was unraveled. This research provides thorough insights on AOCs biodegradation using a step-feed multi-stage alternating anoxic/oxic COW treatment process.
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•Aromatic organic compounds were efficiently removed by SFTIAOB.•Spectrum characterization reveals functional groups, molecular structure changes of AOCs.•Carboxylation, ring-cleavage and mineralization were observed during AOCs biodegradation.•Specific microbes and key genes related to AOC degradation were identified.•Potential AOCs biodegradation mechanisms under alternating anoxic/oxic were proposed.
In this article, the novel adaptive neural networks (NNs) tracking control scheme is presented for nonlinear partial differential equation (PDE)-ordinary differential equation (ODE) coupled systems ...subject to deception attacks. Because of the special infinite-dimensional characteristics of PDE subsystem and the strong coupling of PDE-ODE systems, it is more difficult to achieve the tracking control for coupled systems than single ODE system under the circumstance of deception attacks, which result in the states and outputs of both PDE and ODE subsystems unavailable by injecting false information into sensors and actuators. For efficient design of the controllers to realize the tracking performance, a new coordinate transformation is developed under the backstepping method, and the PDE subsystem is transformed into a new form. In addition, the effect of the unknown control gains and the uncertain nonlinearities caused by attacks are alleviated by introducing the Nussbaum technology and NNs. The proposed tracking control scheme can guarantee that all signals in the coupled systems are bounded and the good tracking performance can be achieved, despite both sensors and actuators of the studied systems suffering from attacks. Finally, a simulation example is given to verify the effectiveness of the proposed control method.
•An efficient data-driven algorithm is proposed to identify the system dynamics.•The internal model of the exosystem is embedded in the adaptive fault-tolerant law for the first time.•The obtained ...stability criterion is less conservative than before.
In this paper, the adaptive fault-tolerant output regulation for the system with unknown dynamics is considered. Firstly, a data-driven algorithm is proposed to identify the system dynamics by solving the Riccati equation. Due to unneeded to solve the optimal controller, the iterative process of the algorithm is reduced. Based on the identified model, an adaptive controller is designed to compensate for the actuator faults which include both outage and loss-of-effectiveness faults. Moreover, the internal model of the exosystem is embedded in the adaptive fault-tolerant controller which can stabilize the system whether the actuator faults hold or not. Finally, the numerical simulation result shows the effectiveness of the proposed controller.
