Search

This paper investigates the cooperative output regulation (COR) of nonlinear multi-agent systems (MASs) with long input delay based on periodic event-triggered mechanism. Compared with other mechanisms, periodic event-triggered control can automatically guarantee a Zeno-free behavior and avoid the continuous monitoring of triggered conditions. First, a new periodic event-triggered distributed observer, which is based on the fully asynchronous communication data, is proposed to estimate the leader information. Second, a new distributed predictor feedback control method is proposed for the considered nonlinear MASs with input delay. By coordinate transformation, the MASs are mapped into new coupled ODE-PDE target systems with some disturbance-like terms. Then, we show that the COR problem is solvable. At last, to further save the communication resource, a periodic event-triggered mechanism is considered in the sensor-to-controller transmission in every agent. A new periodic event-triggered filter is proposed to deal with the periodic event-triggered feedback data. The MASs with input delay are mapped into coupled ODE-PDE target systems with sampled data information. Then, Lyapunov-Krasovskii functions are constructed to demonstrate the exponential stability of the MASs. Simulations verify the validity of the proposed results., Comment: Acceptted by IEEE Trans. Automatic Control

This article focuses on the trajectory tracking problem of mobile manipulators (MMs). Firstly, we construct a position and orientation model predictive tracking control (POMPTC) scheme for mobile manipulators. The proposed POMPTC scheme can simultaneously minimize the tracking error, joint velocity, and joint acceleration. Moreover, it can achieve synchronous control for the position and orientation of the end-effector. Secondly, a finite-time convergent neural dynamics (FTCND) model is constructed to find the optimal solution of the POMPTC scheme. Then, based on the proposed POMPTC scheme, a non-singular fast terminal sliding model (NFTSM) control method is presented, which considers the disturbances caused by the base motion on the manipulator at the dynamic level. It can achieve finite-time tracking performance and improve the anti-disturbances ability. Finally, simulation and experiments show that the proposed control method has the advantages of strong robustness, fast convergence, and high control accuracy., Comment: This article consists of 13 pages, including the text and the proof process

Relativistic heavy-ion collisions give rise to the formation of both deconfined QCD matter and a strong magnetic field. The spin of heavy quarks is influenced by interactions with the external magnetic field as well as by random scatterings with thermal light partons. The presence of QCD matter comprising charged quarks can extend the lifetime and strength of the magnetic field, thereby enhancing the degree of heavy quark polarization. However, the random scatterings with QCD matter tend to diminish heavy quark polarization. In this study, we utilize the Landau-Lifshitz-Gilbert (LLG) equation to investigate both these contributions. Taking into account the realistic evolutions of medium temperatures and the in-medium magnetic fields at the Relativistic Heavy-Ion Collider (RHIC) and the Large Hadron Collider (LHC), we observe that heavy quark polarization is limited by the short lifetime of the magnetic field and the high temperatures of the medium. Furthermore, we explore the mass dependence of quark polarization, revealing that the polarization degree of strange quarks is much larger than that of charm quarks., Comment: 7 pages, 13 figures

We study the momentum and centrality dependence of the non-prompt $J/\psi$ nuclear modification factors ($R_{AA}$), which comes from the $B$ hadrons decay, in Pb-Pb collisions at the Large Hadron Collider. Bottom quarks are produced in the parton hard scatterings and suffer energy loss in the quark-gluon plasma and the hadronic gas, where the spatial and time evolution of the medium is described with the hydrodynamic equations. Medium-induced elastic scatterings and the radiation in bottom quarks are included in the energy loss of bottom quarks. The hadronization process of bottom quarks is described with the instantaneous coalescence model. After considering both cold and hot nuclear matter effects in Pb-Pb collisions at $\sqrt{s_{NN}}=5.02$ TeV, we calculated the $R_{AA}$ and also the elliptic flows of non-prompt $J/\psi$ from the decay of $B$ mesons at different centralities and transverse momentum bins. The $R_{AA}$ and $v_2$ of non-prompt $J/\psi$ sensitive to the hot medium reflect and centrality supply an opportunity to study the bottom quarks energy loss in the hot medium., Comment: 7 pages, 6 figures

As an alternative but unified and more fundamental description for quantum physics, Feynman path integrals generalize the classical action principle to a probabilistic perspective, under which the physical observables' estimation translates into a weighted sum over all possible paths. The underlying difficulty is to tackle the whole path manifold from finite samples that can effectively represent the Feynman propagator dictated probability distribution. Modern generative models in machine learning can handle learning and representing probability distribution with high computational efficiency. In this study, we propose a Fourier-flow generative model to simulate the Feynman propagator and generate paths for quantum systems. As demonstration, we validate the path generator on the harmonic and anharmonic oscillators. The latter is a double-well system without analytic solutions. To preserve the periodic condition for the system, the Fourier transformation is introduced into the flow model to approach a Matsubara representation. With this novel development, the ground-state wave function and low-lying energy levels are estimated accurately. Our method offers a new avenue to investigate quantum systems with machine learning assisted Feynman Path integral solving.

This study focuses on periodic event-triggered (PET) cooperative output regulation problem for a class of nonlinear multi-agent systems. The key feature of PET mechanism is that event-triggered conditions are required to be monitored only periodically. This approach is beneficial for Zeno behavior exclusion and saving of battery energy of onboard sensors. At first, new PET distributed observers are proposed to estimate the leader information. We show that the estimation error converges to zero exponentially with a known convergence rate under asynchronous PET communication. Second, a novel PET output feedback controller is designed for the underlying strict feedback nonlinear multi-agent systems. Based on a state transformation technique and a local PET state observer, the cooperative semi-global output regulation problem can be solved by the proposed new control design technique. Simulation results of multiple Lorenz systems illustrate that the developed control scheme is effective., Comment: 35 pages, 5 figures, Accepted by IEEE Transactions on Automatic Control

This paper addresses a distributed optimization problem in a communication network where nodes are active sporadically. Each active node applies some learning method to control its action to maximize the global utility function, which is defined as the sum of the local utility functions of active nodes. We deal with stochastic optimization problem with the setting that utility functions are disturbed by some non-additive stochastic process. We consider a more challenging situation where the learning method has to be performed only based on a scalar approximation of the utility function, rather than its closed-form expression, so that the typical gradient descent method cannot be applied. This setting is quite realistic when the network is affected by some stochastic and time-varying process, and that each node cannot have the full knowledge of the network states. We propose a distributed optimization algorithm and prove its almost surely convergence to the optimum. Convergence rate is also derived with an additional assumption that the objective function is strongly concave. Numerical results are also presented to justify our claim.

Lithium metal has been an attractive candidate as a next generation anode material. Despite its popularity, stability issues of lithium in the liquid electrolyte and the formation of lithium whiskers have kept it from practical use. Three-dimensional (3D) current collectors have been proposed as an effective method to mitigate whiskers growth. Although extensive research efforts have been done, the effects of three key parameters of the 3D current collectors, namely the surface area, the tortuosity factor, and the surface chemistry, on the performance of lithium metal batteries remain elusive. Herein, we quantitatively studied the role of these three parameters by synthesizing four types of porous copper networks with different sizes of well-structured micro-channels. X-ray microscale computed tomography (micro-CT) allowed us to assess the surface area, the pore size and the tortuosity factor of the porous copper materials. A metallic Zn coating was also applied to study the influence of surface chemistry on the performance of the 3D current collectors. The effects of these parameters on the performance were studied in detail through Scanning Electron Microscopy (SEM) and Titration Gas Chromatography (TGC). Stochastic simulations further allowed us to interpret the role of the tortuosity factor in lithiation. By understanding these effects, the optimal range of the key parameters is found for the porous copper anodes and their performance is predicted. Using these parameters to inform the design of porous copper anodes for Li deposition, Coulombic efficiencies (CE) of up to 99.56% are achieved, thus paving the way for the design of effective 3D current collector systems.

This paper concentrates on the study of the decentralized fuzzy control method for a class of fractional-order interconnected systems with unknown control directions. To overcome the difficulties caused by the multiple unknown control directions in fractional-order systems, a novel fractional-order Nussbaum function technique is proposed. This technique is much more general than those of existing works since it not only handles single/multiple unknown control directions but is also suitable for fractional/integer-order single/interconnected systems. Based on this technique, a new decentralized adaptive control method is proposed for fractional-order interconnected systems. Smooth functions are introduced to compensate for unknown interactions among subsystems adaptively. Furthermore, fuzzy logic systems are utilized to approximate unknown nonlinearities. It is proven that the designed controller can guarantee the boundedness of all signals in interconnected systems and the convergence of tracking errors. Two examples are given to show the validity of the proposed method.

This study considers the problem of periodic event-triggered (PET) cooperative output regulation for a class of linear multi-agent systems. The advantage of the PET output regulation is that the data transmission and triggered condition are only needed to be monitored at discrete sampling instants. It is assumed that only a small number of agents can have access to the system matrix and states of the leader. Meanwhile, the PET mechanism is considered not only in the communication between various agents, but also in the sensor-to-controller and controller-to-actuator transmission channels for each agent. The above problem set-up will bring some challenges to the controller design and stability analysis. Based on a novel PET distributed observer, a PET dynamic output feedback control method is developed for each follower. Compared with the existing works, our method can naturally exclude the Zeno behavior, and the inter-event time becomes multiples of the sampling period. Furthermore, for every follower, the minimum inter-event time can be determined \textit{a prior}, and computed directly without the knowledge of the leader information. An example is given to verify and illustrate the effectiveness of the new design scheme., Comment: 17 pages, 13 figures, submitted to Automatica. accepted

This paper investigates the finite time stabilization problem for a class of nonlinear systems with unknown control directions and unstructured uncertainties. The unstructured uncertainties indicate that not only the parameters but also the structure of the system nonlinearities are uncertain. The contributions are mainly in the following two aspects: First, a new adaptive control method is proposed for the considered system. Logic-based switching rule is utilized to tune the controller parameters online to stabilize the system in finite time. Different from the existing adaptive controllers for structured/parametric uncertainties, a new switching barrier Lyapunov method and supervisory functions are introduced to overcome the obstacles caused by unstructured uncertainties and unknown control directions. Second, based on a time-varying backstepping scheme, an extension is made to the proposed method such that all the system states can be regulated to zero in prescribed finite time. Moreover, a new analysis tool is presented to show the boundedness of the control signals. Simulations are conducted to verify the effectiveness of the proposed methods., Comment: 33 pages, 8 figures. This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible