The generalized homogenization-based protocol is proposed, which provides a novel direction for the challenging problem of finite-time consensus tracking (FTCT) control in singular multiagent systems (SMASs) in this paper. The proposed FTCT protocol is continuous and can be regarded as an upgrade of the distributed protocol for asymptotically stable analysis. Then, the homogeneity conditions of the closed-loop systems under the proposed protocol are derived, providing an important prerequisites for FTCT analysis. The FTCT problem for SMASs is successfully addressed by combining the construction of canonical homogeneous norm Lyapunov function and impulse free analysis. Finally, the simulation results are provided to validate the effectiveness of the proposed method.

This paper investigates the low-complexity predefined-time (PT) optimal formation control (FC) of multi-nonholonomic mobile robots (MNMRs) with collision avoidance safety requirements. Firstly, by applying the funnel technique, the collision avoidance and communication range constraints between adjacent robots are uniformly transformed into formation error constraints, thereby eliminating the complex barrier Lyapunov functions in existing methods and reducing the complexity of controller design. Then, to mitigate the complexity explosion problem, an enhanced nonlinear filter with adaptive parameters is designed, which reduces the computational load while improving the convergence performance of the system. On this basis, the low-complexity safe FC scheme is constructed using broad fuzzy neural networks (BFNNs) and reinforcement learning techniques, achieving PT stability, optimality, avoiding collisions, and no overshoot behavior in formation errors. Finally, the effectiveness and feasibility of the proposed control method are verified on the Speedgoat real-time target machine.

This paper focuses on the problem of adaptive predefined-time control for nonstrict-feedback nonlinear systems with sensor and actuator attacks under dynamic event-triggered framework. The property of the fuzzy logic system is employed to address the algebraic loop problem deriving from the nonstrict-feedback form. The command filter and the error compensation mechanism are devised to eliminate the “explosion of complexity” problem and the effect of filtered error in a predefined time, respectively. By means of the Nussbaum gain technique and modified coordinate transformation, the unknown control gains of the sensor and actuator induced by the deception attacks are resolved. By constructing a dynamic variable, a dynamic event-triggered mechanism is devised to reduce resource consumption. It is strictly proved that the closed-loop system is practically predefined-time stable and the output signal converges to a small region near the origin in a predefined time. Finally, a simulation example is utilized to testify the effectiveness and superiority of the proposed predefined-time control algorithm.

This article concentrates on the problem of practically time-synchronized tracking control for multi-input multi-output (MIMO) systems with unmatched nonlinearities and input saturations. Different from the existing approaches, a practically time-synchronized command filtered backstepping (CFB) control scheme is proposed. By integrating modified command filters and control signals designed with norm-normalized sign functions, the newly developed framework not only retains the advantages of the CFB control approach but also guarantees the property of time-synchronized convergence. Specifically, the "explosion of complexity" phenomenon and the influence of filtering errors are simultaneously addressed, and all components of the tracking error can achieve practically synchronous convergence to a small neighborhood of the origin in a finite time, despite the presence of unmatched nonlinearities in high-order systems. Furthermore, novel auxiliary systems are recursively embedded into each step of the time-synchronized CFB design to counteract the effect of input saturation. Rigorous theoretical analyses and comparative simulations demonstrate the rationality, effectiveness, and superiority of the proposed control scheme.

This paper investigates the predefined-time (PT) formation control for heterogeneous vehicle systems with general narrow tunnel constraints and non-affine actuator faults. Unlike conventional barrier Lyapunov function-based approaches that rely on specific constraint forms, a novel funnel-based control framework is developed to directly accommodate general curvilinear constraint boundaries. To address the explosion of complexity issue, an enhanced nonlinear filter is proposed, which reduces parameter dependence while improving filtering accuracy. By combining funnel control, coordinate transformations, and Butterworth low-pass filter, an adaptive broad fuzzy neural network control strategy is constructed to ensure PT stability of the closed-loop system. Besides, the proposed approach guarantees safe vehicle operation under narrow-tunnel constraints while keeping formation errors within prescribed performance funnels. Real-time experiments on a Speedgoat platform validate the effectiveness and feasibility of the proposed method.

Traditional Lyapunov stability theory cannot directly apply to constrained stochastic nonlinear systems when using barrier Lyapunov functions due to their inherent lack of radial unboundedness. This article presents a novel approach to establishing finite-time stability for such systems by employing Lyapunov functions. The proposed stability analysis relies on a time-varying gain function that remains uniformly bounded. This approach ensures that the system achieves finite-time stability with an arbitrarily prescribed upper bound on the settling time, thereby effectively avoiding the unbounded controller gain problem. The resulting stability is further extended to the finite-time state-feedback control for strict-feedback stochastic nonlinear systems with output constraints. Simulation studies validate the effectiveness of the proposed control scheme.

This article investigates the finite-time switching control issue based on switched observer for networked discrete implicit systems under dynamic event-triggered protocol (DETP) and denial-of-service (DoS) attacks. First, regarding the intermittent characteristic of DoS attacks, a switched observer adapted to such attacks is devised to tackle the unavailability of state information. In addition, to enhance the efficiency of network resource utilization, an improved DETP is introduced, which not only relies on the latest transmission data and the current sampling data, but also combines the changes in their average values to dynamically adjust the triggering threshold. Next, by adopting the singular value decomposition approach, the iterative technique and by constructing the Lyapunov-Krasovskii (L-K) functional correlated with the DoS attack signals, the criteria of singular finite-time boundedness for the networked controlled implicit systems are acquired. The proposed cooperative scheme for DETP and observer-based switching controller promotes both communication efficiency and the resilience of the implicit systems to DoS attacks. Finally, the validity of the mentioned collaborative design switching control method is confirmed by taking direct current motor model and tunnel diode circuit as simulation examples.

This paper investigates the adaptive event-triggered data-driven control problem for a class of unknown nonlinear discrete networked systems. To address this problem, a stochastic configuration network-based algorithm is developed to construct a candidate mapping set within the modeling-valid domain. Subsequently, an adaptive event-triggered control protocol is proposed, and a closed-loop mapping set is obtained. Then, by leveraging the ideas of transfer stabilization and the S-lemma, a data-driven stability criterion for nonlinear discrete networked systems is derived. The stability criterion solely relies on the data of the controlled system and is independent of both the system model and the data model. Based on this stability criterion, the control gain and triggering matrix of the controlled system can be obtained. Additionally, the effectiveness and practicality of the proposed method are validated through a numerical example and a complex memristive Hopfield neural network circuit.

In this article, global adaptive quantized control problem of a class of nonlinear uncertain systems with sensor faults is addressed, and a novel non-identification adaptive control method is proposed based on a switching mechanism. One advantage of the proposed method is that continuous multiplicative sensor faults are tolerated and handled in a generalized Lyapunov matrix inequality; another is its lower computational complexity compared to the traditional adaptive backstepping method (avoiding the ‘differential explosion’ problem). In addition, a new hysteresis logarithmic-type quantizer is developed to prevent chattering. The quantization error is dealt with by using sector bounded property, where the compensation of multiplicative deviation in quantization is similar to that of multiplicative sensor faults, while additive bias is treated as a disturbance (quantization dead-zone size determines the magnitude of the disturbance). Especially, the relationship between quantization dead-zone and control accuracy is clearly characterized. Also, it is shown that the proposed control method is robust to mismatched disturbances, and the solutions of the closed-loop system can be guaranteed to converge to the arbitrarily small neighborhood of the origin as long as the dead-zone of quantizer and mismatched disturbances are sufficiently small.

This article focuses on the problem of predefined-time adaptive output-feedback tracking control with prescribed performance for a quadrotor unmanned aerial vehicle (QUAV). Fuzzy logic systems (FLSs) are utilized to identify the unknown nonlinear dynamics of QUAV, and a fuzzy state observer is devised to estimate immeasurable states. By using the command filter, the problem of “explosion of complexity” is successfully averted, meanwhile the influence of filtered error is eliminated by way of the fractional power error compensation mechanism. The issue of singularity is effectively tackled by the hyperbolic tangent function's property and L'Hospital's rule. A predefined-time performance function is inserted into the control scheme to ensure that the tracking errors are restricted to the preassigned performance bounds. It is strictly proven that the closed-loop system is practically predefined-time stable, and the position and attitude tracking errors are driven into a small region around zero in a predefined time. Finally, a comparative simulation example is provided to show the validity and superiority of the proposed predefined-time adaptive control algorithm.

This article concentrates on the distributed fixed-time adaptive event-triggered attitude control problem for multiple quad-rotor unmanned aerial vehicles (QUAVs) with prescribed performance. By utilizing the fuzzy logic system and constructing a piecewise continuous function, the unknown nonlinear dynamics of multiple QUAVs and the problem of singularity are skillfully addressed, respectively. The command filter that has fixed-time convergence is devised to avert the “explosion of complexity” problem, while the impact of filtered error is eliminated by virtue of the fractional-power-based error compensation signals. Moreover, a fixed-time performance function is embedded into the distributed attitude control algorithm to ensure that the synchronization errors converge to the preassigned performance confines. It is strictly proved that all closed-loop signals are fixed-time bounded, and the disagreement errors are steered into a small region nearby the zero in a fixed time. Finally, numerical simulations are given to demonstrate the efficiency and superiority of the devised fixed-time control scheme.Note to Practitioners—This article aims at designing an event-triggered distributed attitude control algorithm to relax the communication burden for multiple QUAVs subject to external disturbances. In practical applications, the communication bandwidth and the onboard energy of QUAVs are limited, while the traditional time-triggered approaches neglect these realistic restrictions. Thereby, by incorporating a relative threshold event-triggered mechanism into the command filtered backstepping design process, not only can the “explosion of complexity” issue and the impact of filtered error be surmounted, but also the frequency of controller updating is reduced. Additionally, the construction of a prescribed performance function with fixed-time convergence results in the improvement of both transient and steady-state performances for multiple QUAVs, thus meeting practical requirements more effectively.

This article focuses on the predefined-time adaptive fuzzy bipartite consensus control problem for multiquadrotors (MQs) under malicious attacks. The unknown nonlinear dynamics of MQs are effectively identified via the approximation capability of fuzzy logic systems. By integrating the command filter and the error compensation mechanism into the backstepping design procedure, the “explosion of complexity” issue and the effect of filtered error are concurrently eliminated. Additionally, the problem of singularity is skillfully surmounted by the feature of hyperbolic tangent functions and L'Hospital's rule. To deal with unknown malicious attacks, the quadratic-fraction actual controllers for MQs are devised based on the adaptive technique, where the lower bounds of attack signals are not required. It is proven that the closed-loop system is practically predefined-time stable, and the bipartite consensus errors converge into a small neighborhood of the origin within a predefined time. A simulation example is conducted to verify the effectiveness and superiority of the developed predefined-time control strategy.

The issue of optimal output feedback control of uncertain nonlinear systems with quantized input is considered in this work. The fuzzy logic system is employed to approximate unknown nonlinearities and optimal cost. By incorporating the observer technique into command filtered backstepping control framework, the feedforward quantized control signal is designed. Then, the optimal feedback control signal for the constructed affine system is derived via single network adaptive dynamic programming. Finally, an optimal output feedback quantized control scheme is proposed. With the aid of adaptive compensating technique, the requirement for prior knowledge of quantization parameter is eliminated. The boundedness of all the signals in the closed-loop system is proved, and the output of system can reach the reference trajectory. Comparative simulations are implemented to verify the effectiveness of the proposed control strategy.

This article considers the problem of finite-time adaptive fuzzy prescribed performance control (PPC) via output-feedback for nonstrict-feedback nonlinear systems. The fuzzy state observer is designed to estimate the unmeasured system states. To rapidly approximate the derivative of virtual signal, a novel finite-time command filter is proposed. The fractional power error compensation mechanism is established to remove filtered error. By integrating the PPC and command filter technique into backstepping recursive design, a finite-time adaptive output-feedback controller is constructed, and the stability of closed-loop system is strictly proved. The designed control strategy shows that the closed-loop system is practical finite-time stable, and the output tracking error converges to a residual set within prescribed performance bound in finite time. Finally, a numerical comparison and practical examples are provided to demonstrate the validity of the developed finite-time control algorithm.

In this article, the problem of finite-time adaptive fuzzy tracking control for multi-input and multi-output (MIMO) nonlinear systems with input saturation is investigated. The new finite-time command filter is introduced for generating command signals and their derivatives to work out the matter of “explosion of complexity,” and the modified fractional power-based error compensation mechanism (ECM) serves as removing the effect of filter error. Then, the finite-time adaptive control scheme is established via the backstepping recursive design technique. It guarantees all the signals of the closed-loop system (CLS) are finite-time bounded while the output tracking errors are regulated to a sufficiently small neighborhood of the origin in finite time. Finally, the effectiveness of the proposed finite-time control scheme is verified by a numerical comparison example.