Search

To address the issues of motion disturbance and low loading accuracy in electro-hydraulic load simulation systems, and to effectively mitigate the impact of uncertainty on system performance, this paper proposes a novel independent load port electro-hydraulic load simulation system. A nonlinear variable structure state equation is derived to describe the pressure working states of the left and right chambers of the servo valve and hydraulic cylinder under loading conditions. In light of the presence of substantial motion disturbances, an integrated sliding mode automatic disturbance rejection composite controller is proposed with a focus on fixed-time convergence. To mitigate system chattering and enhance system loading performance and disturbance immunity, a fixed-time integral sliding mode controller was developed within the framework of active disturbance rejection control. Stability analysis was also carried out. Simulation research demonstrates that the pressure control accuracy of the composite controller is 99.88%, 99.86%, and 99.83% respectively when the system step command is given with disturbance frequencies of 1 Hz, 3 Hz, and 5 Hz. Similarly, under the same disturbance frequencies, the pressure control accuracy is 99.88%, 99.86%, and 99.84% respectively when the system sine command is given. The simulation results demonstrate that the independent load port electro-hydraulic load simulation system exhibits a notable energy-saving effect. Specifically, energy savings of around 45% and 48% were achieved compared to the original system. The research and exploration conducted have laid a strong groundwork for future in-depth studies on the independent load port electro-hydraulic load simulation system. [ABSTRACT FROM AUTHOR]

Abstract To address the issues of motion disturbance and low loading accuracy in electro-hydraulic load simulation systems, and to effectively mitigate the impact of uncertainty on system performance, this paper proposes a novel independent load port electro-hydraulic load simulation system. A nonlinear variable structure state equation is derived to describe the pressure working states of the left and right chambers of the servo valve and hydraulic cylinder under loading conditions. In light of the presence of substantial motion disturbances, an integrated sliding mode automatic disturbance rejection composite controller is proposed with a focus on fixed-time convergence. To mitigate system chattering and enhance system loading performance and disturbance immunity, a fixed-time integral sliding mode controller was developed within the framework of active disturbance rejection control. Stability analysis was also carried out. Simulation research demonstrates that the pressure control accuracy of the composite controller is 99.88%, 99.86%, and 99.83% respectively when the system step command is given with disturbance frequencies of 1 Hz, 3 Hz, and 5 Hz. Similarly, under the same disturbance frequencies, the pressure control accuracy is 99.88%, 99.86%, and 99.84% respectively when the system sine command is given. The simulation results demonstrate that the independent load port electro-hydraulic load simulation system exhibits a notable energy-saving effect. Specifically, energy savings of around 45% and 48% were achieved compared to the original system. The research and exploration conducted have laid a strong groundwork for future in-depth studies on the independent load port electro-hydraulic load simulation system.

In this paper, the fixed-/preassigned-time anti-synchronisation problem is studied for delayed memristive neural networks (DMNNs) with discontinuous activation functions and external disturbance. First of all, several simple controllers are structured for the fixed-time anti-synchronisation (FTAS) of DMNNs with discontinuous activation functions. Moreover, an effective and convenient control scheme for preassigned-time anti-synchronisation (PTAS) is presented by modifying the controller parameters. The proposed control scheme is also available for DMNNs with continuous activation functions or without time delays. In addition, sufficient conditions for FTAS and PTAS of DMNNs are derived and the accurate estimation for settling-time is given. Finally, simulation examples are presented to verify the validity of the main results. [ABSTRACT FROM AUTHOR]

This paper proposes a novel neural network-based control algorithm with fixed-time performance constraints for manipulator systems in workspaces. The algorithm efficiently controls the manipulator's trajectory tracking by tuning a preset performance function, thereby optimizing both speed and accuracy within a fixed timeframe. Initially, a tangent-type error transformation, applied through homogeneous embryonic transformation, ensures rapid convergence of tracking errors to a specific region. Subsequently, integrating a predetermined control strategy into the fixed-time stability framework ensures the system's state reaches a defined boundary within a finite period. Lastly, neural networks are employed to approximate dynamic parameters and adjust the controller, achieving optimal parameter approximation and significantly enhancing trajectory tracking robustness. Simulation analyses and comparisons confirm the controller's effectiveness and superiority in enhancing both the transient and steady-state performance of the control system. [ABSTRACT FROM AUTHOR]

A cart-pendulum system is a typical underactuated mechanical system with two degrees of freedom and one control input. The fixed-time stabilization control problem for this system is studied in this paper. A fixed-time hierarchical sliding mode control method is developed to solve this problem. Firstly, the system is divided into two subsystems. And two first-level sliding mode surfaces are designed for these two subsystems respectively. Secondly, a second-level sliding mode surface is constructed by linearly combining two first-level sliding mode surfaces. After that, a hierarchical sliding mode controller is designed based on the designed sliding mode surfaces. It enables the state variables of closed-loop control system to be stabilized at the origin within a fixed-time. This means that the settling time can be limited within a range and does not depend on the initial state value of the system. Finally, a numerical example is given to show the effectiveness of the developed control method. [ABSTRACT FROM AUTHOR]

The fixed time control problem for the secondary voltage and frequency of islanded AC microgrids is studied. Based on the multi-agent consensus method, an adaptive fuzzy fixed-time secondary voltage controller considering state constraints and the secondary frequency controller based on control barrier function are proposed. In multi-agent consensus control, each distributed generation is regarded as a nonlinear agent, and the agents communicate with each other through a sparse network. In designing the voltage controller, the adaptive fuzzy estimation of the unknown variables after feedback linearization is used to improve the adaptive ability of the controller and a new sliding mode surface is introduced to make the voltage converge in fixed time. Considering the problem of system state constraints, the barrier Lyapunov function and the control barrier function are used to design the voltage and frequency controllers respectively, so that the system state is within the preset constraint range. The sharing of active power and reactive power is also considered. A proof about fixed time convergence and stability is given. Under the environment of MATLAB/SimPowerSystem, the effectiveness of the proposed controller is verified by the simulation about the load variations and large disturbance of microgrids. [ABSTRACT FROM AUTHOR]

Copyright of Control Theory & Applications / Kongzhi Lilun Yu Yinyong is the property of Editorial Department of Control Theory & Applications and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In this paper, a fixed-time adaptive fuzzy control scheme is investigated to stabilize a class of uncertain nonlinear systems with full-state constraints. A novel secant barrier Lyapunov function (SBLF) is first constructed to design the controller and obtain the fixed-time stability properties by using the (SBLF) in the design process of back-stepping. The adaptive controller is presented to guarantee that the tracking errors of the system can converge into the neighborhood around the equilibrium point in a fixed time and all the system states can be restricted within the predefined time-varying boundaries. By making use of Lyapunov analysis, we can prove that all the signals in the closed loop system are uniformly ultimately bounded and the output is well driven to follow the desired trajectory. Finally, simulations are given to verify the effectiveness of the method. [ABSTRACT FROM AUTHOR]

Backstepping-based fixed-time tracking control is proposed for a robotic arm system to solve the problem of trajectory tracking control under system uncertainties, which ensures the robotic arm system can realize stable tracking control within a fixed time independent of the initial state of the system. In addition, to address the uncertainties in the robotic arm system, a control strategy based on disturbance observer compensation is designed, which provides feed-forward compensation through the accurate estimation of the system uncertainties and enhances the system's robustness. Finally, a two-link robotic arm model is used for simulation experiments, and the comparison results show that the control scheme designed in this article can effectively improve the robotic arm's tracking accuracy and convergence speed. [ABSTRACT FROM AUTHOR]

A novel zeroing neural network control scheme based on an extended state observer is proposed for the trajectory tracking of a tracked mobile robot which is subject to unknown external disturbances and uncertainties. To estimate unknown lumped disturbances and unmeasured velocities, a third-order fixed-time extended state observer is proposed, and the observation errors converge to zero in fixed time. Based on the estimated values, the zeroing neural network controller is designed for a tracked mobile robot to track an eight shape. The stability of the system is analyzed based on Lyapunov theory. Simulation results are illustrated to show the effectiveness of the proposed control scheme. [ABSTRACT FROM AUTHOR]

In this paper, fixed‐time synchronization of nonlinear stochastic coupling multilayer neural networks is studied. The neural subnets in the multilayer networks are delay Cohen–Grossberg neural networks (DCGNNs). To overcome uncertain factors, we designed an adaptive delay‐dependent controller in synchronization. To describe constraints of communication and other related problems in networks, which are due to limitations for bit rates and bandwidths in communication channels, an adaptive fixed‐time control strategy is purposed by introducing quantization signal input. A theoretical framework about fixed‐time synchronization in multilayer delay Cohen–Grossberg neural networks (MDCGNNs) is established. We find that fixed settling time is related to the scale of MDCGNNs, characteristics of the designed controller parameters, and level of quantization. Finally, the effective of the theoretical framework is validated in an example. [ABSTRACT FROM AUTHOR]

This paper proposes a novel neural network-based control algorithm with fixed-time performance constraints for manipulator systems in workspaces. The algorithm efficiently controls the manipulator’s trajectory tracking by tuning a preset performance function, thereby optimizing both speed and accuracy within a fixed timeframe. Initially, a tangent-type error transformation, applied through homogeneous embryonic transformation, ensures rapid convergence of tracking errors to a specific region. Subsequently, integrating a predetermined control strategy into the fixed-time stability framework ensures the system’s state reaches a defined boundary within a finite period. Lastly, neural networks are employed to approximate dynamic parameters and adjust the controller, achieving optimal parameter approximation and significantly enhancing trajectory tracking robustness. Simulation analyses and comparisons confirm the controller’s effectiveness and superiority in enhancing both the transient and steady-state performance of the control system.

Considering that in the trajectory tracking control of a nonlinear robotic manipulator system, the control effect is easily limited by the initial state of the system, and the system has modeling error, unknown disturbance, and friction in the actual control, to overcome the above problems, a fixed‐time sliding mode control (SMC) strategy based on adaptive disturbance observer (ADO) is developed in this paper. Firstly, feedforward compensation of the system is achieved by developing an ADO to accurately estimate the compound disturbances in the system. Second, a new fixed‐time sliding mode (SM) surface is presented to overcome the singularity issue and accelerate the error convergence. In addition, to enhance the performance of the reaching phase, a variable exponential power reaching law (VEPRL) is developed, which can effectively adjust the convergence rate. Through rigorous theoretical analysis, it is shown that the system state can be stabilized at a fixed time, and an upper bound on the convergence time is also given. Finally, the effectiveness of the control method is verified by comparing it with different control schemes in simulation. [ABSTRACT FROM AUTHOR]

This paper proposes a fixed‐time backstepping distributed cooperative control scheme based on fixed‐time extended state observer (FxTESO) for multiple unmanned aerial vehicles (UAVs). A fixed‐time ESO, which is convergent independently of initial conditions, is designed to estimate and compensate the external disturbances in tracking process. Moreover, to eliminate the "explosion of complexity" in the traditional backstepping architecture, a nonlinear first‐order filter is adopted to construct the distributed fixed‐time control scheme. Based on the local information of neighboring UAVs, a fixed‐time backstepping cooperative controller is designed. The proposed formation algorithm can be shown practicable for the UAV control system by using of Lyapunov stability theory and graph theory. Simulation results are given to demonstrate the effectiveness of the proposed control scheme. [ABSTRACT FROM AUTHOR]

In this paper, the fixed-time multi-switch combination–combination synchronization (FTMSCCS) of fractional-order chaotic systems with uncertainties and external disturbances is studied. The appropriate sliding mode surface and controller are proposed based on a Lyapunov theorem, and fixed-time multi-switching combination–combination synchronizations between four fractional-order chaotic systems are realized. The Lyapunov function is designed to prove the feasibility of the controller theoretically, and the effectiveness and robustness of the synchronization mechanism are further verified by numerical simulations. The advantage of this article is that it extends fixed-time synchronization to multi-switch combination–combination synchronization, enabling synchronization for a limited time, while increasing the complexity of the synchronization mechanism and improving its confidentiality in communication applications. [ABSTRACT FROM AUTHOR]

This paper studies the adaptive fixed-time synchronization issue for convex-delayed neural networks. First, the convex delay is introduced to address the state delay of neural networks in order to reflect the impacts of multiple delay components such as input transition time and switching communication. Then, a new fixed-time control method is presented to adaptively determine multi-control gains with a unified update law. Afterward, some sufficient criteria are figured out by using Lyapunov stability theorem to ensure that the delayed neural networks are fixed-timely stable. Finally, simulated examples are adopted to validate our theoretical results. • The convex delay is introduced to reflect the impacts of multiple delay components. • An adaptive fixed-time control is proposed to uniformly adjust the feedback gains. • Sufficient criteria are derived to ensure the fixed-time stability of neural networks. [ABSTRACT FROM AUTHOR]

Copyright of Control Theory & Applications / Kongzhi Lilun Yu Yinyong is the property of Editorial Department of Control Theory & Applications and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The fixed-time stability on uncertain neural networks with adaptive coupling strength is addressed in this paper. To beign with, a new time-varying coupling strength is introduced, which is based on the projective transform of quantized error systems. Next, to address various disturbances in master-slave systems, inhomogeneous uncertainty is taken into consideration. Then, a multi-quantized fixed-time controller is put forward to ensure that the systems reach to a prescribed trajectory in the settling time. Afterward, sufficient synchronization criteria are derived on the strength of the Lyapunov stability theorem. Finally, simulation examples are given to validate the theoretical analysis. [ABSTRACT FROM AUTHOR]

A novel zeroing neural network control scheme based on an extended state observer is proposed for the trajectory tracking of a tracked mobile robot which is subject to unknown external disturbances and uncertainties. To estimate unknown lumped disturbances and unmeasured velocities, a third-order fixed-time extended state observer is proposed, and the observation errors converge to zero in fixed time. Based on the estimated values, the zeroing neural network controller is designed for a tracked mobile robot to track an eight shape. The stability of the system is analyzed based on Lyapunov theory. Simulation results are illustrated to show the effectiveness of the proposed control scheme.

Copyright of Control Theory & Applications / Kongzhi Lilun Yu Yinyong is the property of Editorial Department of Control Theory & Applications and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In this paper, the leader-following consensus of second-order nonlinear multiagent systems (SONMASs) with external disturbances is studied. Firstly, based on terminal sliding model control method, a distributed control protocol is proposed over undirected networks, which can not only suppress the external disturbances, but also make the SONMASs achieve consensus in finite time. Secondly, to make the settling time independent of the initial values of systems, we improve the protocol and ensure that the SONMASs can reach the sliding surface and achieve consensus in fixed time if the control parameters satisfy some conditions. Moreover, for general directed networks, we design a new fixed-time control protocol and prove that both the sliding mode surface and consensus for SONMASs can be reached in fixed time. Finally, several numerical simulations are given to show the effectiveness of the proposed protocols. [ABSTRACT FROM AUTHOR]

A practical fixed-time fault estimation observer strategy for non-linear systems using an unknown input observer scheme is investigated. The external disturbances of non-linear systems are decoupled by an unknown input observer technique; therefore, the constructed error dynamics do not include these disturbances. The fixed-time fault estimation observer is then constructed. Moreover, a non-linear fault estimator with two power functions is proposed to improve the convergence speed of fault estimation. Finally, simulation results of a non-linear Lorenz chaotic system are provided to demonstrate the feasibility of the presented strategy. [ABSTRACT FROM AUTHOR]

This paper investigates the problem of parameter estimation for DC-DC buck converter without current sensors. For the circuit, all the parameters of capacitance, inductance, resistance, and input voltage are unknown. A novel Volterra operator-based fixed-time adaptive algorithm is proposed by using only the output voltage and control input signals. By selecting proper kernel function for the Volterra integral operator, the influence of the system initial values can be eliminated, and the calculation of the derivative of the system output can also be avoided. Strict analysis shows that the proposed estimation algorithm can ensure the estimation errors converge to zero in a fixed time independent of the initial error values. Finally, simulation results with different initial values verify the advantages of the proposed algorithm. [ABSTRACT FROM AUTHOR]

In this paper, the issue of fixed-time cluster synchronization is investigated for the directed community networks. We propose a new Lyapunov function method which leads to the settling time is not only independent of the initial value, but also unrelated to the number and dimensions of nodes in the networks. This means our estimated settling time is more accurate and much tighter than the one in the existing results. By designing the corresponding controllers and using the fixed-time stability theorem, some new criteria are derived to guarantee that the community networks achieve cluster synchronization in fixed time. Finally, an illustrative example with computer simulations is given to verify the theoretical analysis. [ABSTRACT FROM AUTHOR]

We apply a primal-dual simplex algorithm for solving the biobjective min imum cost-time network flow problem such that the total shipping cost and the total shipping fixed time are considered as the first and second objective functions, respectively. To convert the proposed model into a single-objective parametric one, the weighted sum scalarization technique is commonly used. This problem is a mixed-integer programming, which the decision variables are directly dependent together. Generally, the previous works have consid ered the linear biobjective problem with the traditional network flow con straints, while in this paper, corresponding to each flow variable, a binary variable is defined. These zero-one variables are utilized to describe a fixed shipping time for positive flows. The proposed method is successful in finding all supported efficient solutions of a real numerical example.

This paper studies global nonsingular fixed-time terminal sliding mode control (GNFTSMC) for a second-order uncertain permanent magnet synchronous motor (PMSM) system to further improve its speed tracking performance. The newly proposed GNFTSMC consists of a time-dependent terminal sliding surface and a piecewise continuous sliding mode control law. By a time-dependent function constructed from the initial conditions of the system and a predefined time, the sliding surface is always reached at the initial instant and forced to a traditional fast terminal sliding surface after the predefined time. Based on Filippov's stability principles, the globally fixed-time stability of the GNFTSMC is proved. Furthermore, a priori time independent of the initial conditions is derived to estimate the boundary of the settling time of the closed control loop. Then, the control law is analyzed to be always nonsingular. Thus, the GNFTSMC-based speed controller for the PMSM speed tracking system is developed. Finally, simulations are conducted for the proposed controller and other terminal sliding mode controllers. The results show that compared to the other controllers, the PMSM system based on GNFTSMC displays improved performance characteristics of faster speed response, smaller chattering and higher current efficiency.

In this paper, the fixed-time multi-switch combination–combination synchronization (FTMSCCS) of fractional-order chaotic systems with uncertainties and external disturbances is studied. The appropriate sliding mode surface and controller are proposed based on a Lyapunov theorem, and fixed-time multi-switching combination–combination synchronizations between four fractional-order chaotic systems are realized. The Lyapunov function is designed to prove the feasibility of the controller theoretically, and the effectiveness and robustness of the synchronization mechanism are further verified by numerical simulations. The advantage of this article is that it extends fixed-time synchronization to multi-switch combination–combination synchronization, enabling synchronization for a limited time, while increasing the complexity of the synchronization mechanism and improving its confidentiality in communication applications.

Most current methodologies on fixed-time adaptive fuzzy control for uncertain nonlinear systems result in practical fixed-time stability but not fixed-time stability, or require prior knowledge of the system dynamics. To obviate such restrictions, a fixed-time adaptive fuzzy control scheme is newly proposed with the discoveries of a singularity-avoidance virtual control design, a modified class of tuning functions, and a projection operator based adaptation mechanism. Fixed-time stability is established in the sense that the tracking error asymptotically converges to a user-defined interval within a prescribed fixed time. Illustrative examples verify the approaches developed. [ABSTRACT FROM AUTHOR]

This paper deals with the problem of fixed-time attitude tracking control for spacecraft subject to model uncertainties and external disturbances. Firstly, by using a fixed-time extended state observer (FxTESO), the synthetic uncertainties generated by external disturbances and model deviations can be estimated and compensated accordingly. We propose a novel FxTESO aimed to improve previous methods. Compared with the existing extended state observer (ESO), the proposed FxTESO provides faster convergence and higher accuracy. Then, we design a fixed-time adaptive attitude tracking controller based on the strategy combining the FxTESO and fast non-singular terminal sliding mode control (FNTSMC), such that a desired attitude can be achieved accurately, which does not only allow providing fast and accurate responses, and acceptable chattering suppression, but also avoiding singularity. Finally, the numerical simulation results are discussed to verify the efficiency and merits of the proposed control strategy. [ABSTRACT FROM AUTHOR]

This paper considers the fixed-time (FXT) and preassigned-time (PAT) stochastic synchronization of complex dynamic networks (CDN) based on the quantized event-triggered strategy. First, by applying some constructing comparison systems, more relaxed criteria are proposed for FXT stability and the estimated settling time is more accurate. Second, the FXT quantized event-triggered control schemes with sign or saturation function are designed, in which Zeno behavior is excluded and chattering phenomenon is reduced under the control strategies with saturation function. Besides, the quantized event-triggered control schemes can more effectively save resources of communication and computation. Third, several novel quantized event-triggered strategies are designed to achieve PAT synchronization, where the settling time can be preassigned according to realistic situation and is irrelevant with parameters and initial values of CDN. Finally, numerical example proves the rationality of the theories for the FXT and PAT stochastic synchronization of CDN. [ABSTRACT FROM AUTHOR]

A practical fixed-time fault estimation observer strategy for non-linear systems using an unknown input observer scheme is investigated. The external disturbances of non-linear systems are decoupled by an unknown input observer technique; therefore, the constructed error dynamics do not include these disturbances. The fixed-time fault estimation observer is then constructed. Moreover, a non-linear fault estimator with two power functions is proposed to improve the convergence speed of fault estimation. Finally, simulation results of a non-linear Lorenz chaotic system are provided to demonstrate the feasibility of the presented strategy.

This paper presents a fixed time containment protocol within output feedback framework for uncertain nonlinear multiagent systems (MASs) exposed to unknown leader dynamics under switching communication topologies. To characterize dynamic communication links among agents in uncertain environments, a Markov jumping process with partially known transition probability is introduced to circumvent the difficulties of requiring the exact elements of transition rates as a prior. Then, in order to eliminate the necessity of broadcasting local velocity states between neighboring agents over the wireless and reject the comprehensive uncertainties including unknown model nonlinearities, external disturbances as well as switching topology jumps, a fixed time extended state observer (FTESO) only using the relative position information as input data is established for follower agents to achieve a uniform fast and precise estimation capability. A fixed time output feedback containment protocol by means of observer is presented to ensure that individual follower is guided into the geometric area constituted by a fleet of unknown leaders with a consistent convergence time irrelevant of initial conditions. The outstanding features of the developed algorithm are threefold: First, a prescribed fixed time containment consensus with reduced communication burden and enhanced robustness can be implemented. Second, a Markov jumping process with a partially known transition probability is considered to stimulate switching communication topologies. Third, a FTESO is constructed for each agent to realize a fixed-time estimation without requiring accurate modeling information. Finally, the fixed time stabilization of cascaded system is illuminated by applying the Lyapunov-based methods and bi-limit homogeneity. Simulation examples validate the feasibility and strengths of developed control protocol. • A fixed time output feedback containment for uncertain nonlinear MASs under switching communication topologies is studied. • A Markov jump process with partially known transition probability is introduced. • A fixed time extended state observer (FTESO) is established for follower agents. [ABSTRACT FROM AUTHOR]

This brief considers the finite-time and fixed-time time-varying formation tracking (TVFT) problem for multiple dynamic targets. Without requiring at least one well-informed agent to obtain the information of all the targets, each agent is allowed to explore any number of targets according to its own detection capability. Based on local interactions, a couple of distributed TVFT control protocols are proposed for agents to achieve a desired time-varying formation while tracking the convex combination of the states of multiple targets, in a finite and fixed settling time, respectively. Besides, by introducing time-varying parameter designs, the positions and velocities of the targets are free without any constraints. Finally, a numerical example is given to validate the obtained theoretical results. [ABSTRACT FROM AUTHOR]

This paper investigates the fixed-time formation tracking control problem for multi-agent systems with model uncertainties and in absence of leader's velocity measurements. For each follower, a novel fixed-time cascaded leader state observer (FTCLSO) without velocity measurements is first designed to reconstruct the states of the leader. Then, radial basis function neural networks (RBFNNs) are adopted to approximate the model uncertainties online. Based on the proposed FTCLSO and RBFNNs, a novel fixed-time formation control scheme is constructed to address the time-varying formation tracking problem by utilizing fixed-time nonsmooth backstepping technique. The fixed-time convergence of the formation tracking error is guaranteed through Lyapunov stability analysis. Finally, simulation results demonstrate the effectiveness of the proposed formation tracking control scheme. [ABSTRACT FROM AUTHOR]

In this brief, the fixed-time practical distributed average tracking (DAT) problem for multiple nonlinear signals is studied, where the nonlinear signals are with bounded- and Lipschitz-type derivatives respectively. Two fixed-time practical DAT algorithms are proposed for agents with local interactions to track the average of the multiple nonlinear signals within a fixed convergence time by using time-base generator techniques. Different from existing results, the proposed DAT algorithms in this brief are applicable to DAT problems for nonlinear signals with both bounded- and Lipschitz-type derivatives, which keeps more reality. Also, the proposed fixed-time practical DAT algorithms are able to provide an explicit estimation of the upper-bounded convergence time without dependence on initial conditions. The fixed convergence time in the proposed algorithms can be adjusted more flexibly. Finally, some illustrative examples are shown to manifest the validity of the fixed-time practical DAT algorithms. [ABSTRACT FROM AUTHOR]

Copyright of Information & Control is the property of Gai Kan Bian Wei Hui and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper develops a robust adaptive neural practical fixed-time tracking control scheme for Euler-Lagrange systems (ELSs) with unknown dynamics and external disturbances under input saturations. A novel auxiliary dynamic system governed by a smooth piecewise continuous function is constructed to handle the input saturation effect, while promoting to achieve the fixed-time convergence of tracking errors. Moreover, the unknown dynamics of ELSs and the bound vector of unknown external disturbances are synthesized into a compounded uncertain vector in this paper. Here, adaptive neural networks with the ∊ -modification updating laws are employed to only approximate the compounded uncertain vector, rather than each dynamic matrix of ELSs, such that the computational burden of the developed control scheme is significantly reduced. It is theoretically proven that the trajectory tracking is able to be achieved in a fixed time under the developed adaptive neural tracking control scheme, while all signals in the Euler-Lagrange closed-loop tracking control system are bounded. The simulation results on a 2-link robotic manipulator are included to illuminate the effectiveness of our developed tracking control scheme and superiority to a finite-time control scheme. [ABSTRACT FROM AUTHOR]

This paper considers the finite-time and fixed-time bipartite synchronization (FFTBS) of coupled delayed neural networks (CDNNs) under signed graphs. For the structurally balanced or unbalanced network topology, both the goals of FFTBS of CDNNs are achieved simultaneously by a unified discontinuous controller. Some sufficient criterion are obtained to ensure the FFTBS under the new designed protocols, and the corresponding settling times are estimated as well. Finally, two simulations are established to verify the validity and effectiveness of the designs. [ABSTRACT FROM AUTHOR]

In this paper, a terminal fractional-order observer and a terminal disturbance observer is proposed to estimate internal states and external disturbances of the class of fractional-order chaotic systems. The estimation of states within fixed time is achieved by employing a nonlinear feedback in terms of the observer error. The fixed convergence time is not relevant to the initial conditions and can be adjusted to any desired values by tuning the designable parameters. Finally, the numerical simulations are performed on fractional-order chaotic Liu, Chen, and Financial systems to validate the theoretical results. Moreover, some numerical simulations are provided to compare the obtained theoretical results with the other methods in the literature. [ABSTRACT FROM AUTHOR]

The rapid attitude stabilization problem of flexible spacecraft with uncertain inertia and disturbances is investigated. In this article, a sliding mode-based fixed-time control approach is presented with a new fixed-time surface ensuring a faster convergence rate incorporated. This surface has no singularity and can guarantee the settling time to be independent of initial states. An adaptive fixed-time attitude control law is then synthesized, which is continuous and chattering free. It is rigorously proved that the states of the spacecraft attitude system can converge into a small neighborhood after fixed time. A numerical example is presented to validate that the designed scheme is efficient to perform attitude stabilization maneuvers rapidly, whereas high control accuracy is still provided. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Central South University is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)