International Journal of Adaptive Control and Signal Processing最新文献

This paper investigates the attitude consensus control problem of a nonlinear unmanned aerial vehicle (UAV) attitude system subject to deferred performance constraints, external disturbance, and input saturation. The inherent nonlinearities and actuator saturation in UAV dynamics pose significant challenges to control design, particularly when performance guarantees are required under external disturbance and constrained control inputs. To address these challenges, we propose a novel intelligent adaptive fusion control method that incorporates a dynamic memory event-triggered mechanism (DMETM) to reduce communication and computational overhead while maintaining system stability and performance. A novel error-shifting mechanism is developed to overcome singularity challenges in deferred-constrained systems, accompanied by a non-singular funnel control strategy to ensure stable implementation of deferred constraint enforcement. By employing Lyapunov stability theory, the proposed approach effectively handles external disturbance and input saturation, ensuring that the UAV attitude system satisfies predefined performance criteria under these constraints. Finally, simulation results validate the efficacy of the proposed method, demonstrating its ability to achieve robust and efficient attitude control in realistic scenarios.

This study addresses the issue of finite-time observer-based $��{�H�}_{�\infty �}�$ control design for a nonlinear fractional-order system under additive faults and disturbances. The main motive is to construct a nonlinear fractional-order proportional-integral observer such that it simultaneously estimates the states and fault signal. A controller is designed to overcome the mismatch between the quantization parameters, and also the estimated fault signal is incorporated in the control design to eliminate the effects of the fault in the system. Furthermore, by choosing an appropriate Lyapunov function, the results are deduced in terms of linear matrix inequalities, based on which the observer and controller gain values are obtained. Then the viability of the developed controller and observer is verified by numerical simulation results.

This article investigates the distributed fusion (DF) filtering issue for multi-sensor multi-rate systems (MSMRSs) with packet disorders (PDs) under hybrid cyber attacks (HCAs). The PDs caused by random transmission delay are characterized by a random variable that has the known probability distribution, and two groups of Bernoulli random variables are adopted to depict the occurrence of HCAs. To facilitate the design of the filtering scheme, a virtual measurement method is introduced to transform the original multi-rate systems into single-rate systems. The purpose of this paper is to design a new local filtering scheme handling PDs, HCAs as well as stochastic nonlinearities simultaneously, and minimize the upper bound (UB) on each local filtering error covariance (LFEC) by selecting an appropriate gain matrix. By using the mathematical induction method, a sufficient condition is obtained to ensure that each LFEC is uniformly bounded. In addition, local estimates are fused based on the inverse covariance intersection (ICI) fusion method. Finally, it is shown that the proposed fusion filtering algorithm is effective through a simulation experiment.

This study explores the issue of fuzzy adaptive resilient formation control for a marine harbor unmanned transport vehicle (UTV) platoon with partial state information and denial-of-service (DoS) attacks. Fuzzy logic systems (FLSs) are utilized to approximate the nonlinear dynamics of the considered vehicle model, and a fuzzy state observer is established to estimate the vehicle's unmeasurable states. To acquire estimations of unknown leader state information caused by DoS attacks, a distributed resilient formation observer is designed. Then, utilizing the introduced fuzzy state observer and resilient formation observer, a novel fuzzy adaptive output-feedback resilient formation control method is formulated through the command-filtered backstepping control technique. It is established that the proposed control approach can ensure individual stability and achieve convergence of formation tracking errors for the marine harbor UTV platoon under unmeasurable states and DoS attacks. Finally, comparative experiments under identical conditions further demonstrate that the proposed resilient control method can effectively counteract DoS attacks, ensuring platoon stability. In contrast, existing methods without DoS attack resistance result in divergent simulations and unstable platoon behavior, thus verifying the effectiveness of our designed distributed resilient formation controller.

To improve the control performance of an air-floating positioning system, a predefined-precision adaptive terminal sliding mode (PPATSM) control scheme is developed. Explicitly, due to the introduced barrier function (BF), the disturbance's upper bound is not required any longer and the control gain can rapidly adapt itself in accordance with the disturbance variation. This result overcomes the undesired overestimation of the control gain as that in many conventional methods. It also guarantees that the position error of the positioner is enclosed within a frozen bound whose size can be exactly predefined, regardless of the unknown disturbance amplitude. Moreover, to deal with the impacts of input saturation, an auxiliary dynamics is presented in the control design. The introduction of the auxiliary dynamics releases the requirement for selecting an output threshold of the barrier function that is larger than the unknown disturbance. In addition, to improve the positioning speed, a non-singular terminal sliding mode is used for the sliding mode control design rather than the common linear sliding mode, and Lyapunov analysis verifies that finite-time positioning is guaranteed in the presence of input saturation. Simulations and experiments demonstrate that the proposed control benefits in terms of robust control precision against parametric uncertainties and external load variations.

This paper investigates an adaptive finite-time tracking control strategy for nonlinear systems subject to input quantization and actuator faults, integrating prescribed performance control (PPC) with finite-time control (FTC). Firstly, the prescribed performance function is used to ensure that the tracking error of the system meets the prescribed performance standards. Secondly, by utilizing the characteristics of quantized nonlinear sectors and the structural model of actuator faults, and allowing the total number of faults to be infinite, a novel finite-time adaptive estimation technique can be devised to handle the effects caused by actuator faults and quantized inputs. Based on this, an adaptive finite-time tracking controller is designed via backstepping, multi-dimensional Taylor network(MTN), quantized feedback, and finite-time Lyapunov stability theory. The control strategy not only ensures that all signals in the closed-loop system are semi-globally practically finite-time stable (SGPFS), but also that the tracking error of the system can meet the transient and steady-state performance criteria within finite time. Finally, simulation results verify the effectiveness of the proposed control scheme.

This study investigates an adaptive asynchronous event-triggered output-feedback scheme for uncertain nonlinear systems, aiming to achieve exponential stabilization. Typically, these systems permit uncertain control directions and unmeasurable state-dependent rates simultaneously. Firstly, with unmeasurable states rebuilt via the system output and gain samples, the proposed approach integrates the dynamic exponential gain controlled by event-triggering mechanisms, which concurrently address large uncertainties while ensuring exponential state convergence. Secondly, the control architecture incorporates double-sided asynchronous event-triggering mechanisms for sensor-controller and controller-actuator channels, with execution intervals online adjusted based on real-time variations in system outputs, observer states, and dynamic gains to adaptively compensate for sampling/execution errors. Hence, the adaptive asynchronous event-triggered output-feedback scheme is presented, which eventually attains exponential convergence. Finally, the simulation results substantiate the developed control scheme's effectiveness in conserving communication resources.

This paper investigates adaptive finite-time quasi-passification and finite-time stabilization problems for uncertain switched nonlinear systems with parameter uncertainties. Finite-time quasipassivity concept of a switched nonlinear system is first proposed. For each active subsystem, finite-time quasi-passivity is satisfied, while at every switching time, the energy is allowed to increase. Compared with passive systems, the supply rate of a quasi-passive system includes a passivity supply rate and a constant supply rate. Based on this concept, a more general state-dependent switching law and singularity-free adaptive feedback controllers are given to achieve finite-time quasi-passification, even if the subsystem is not feedback finite-time quasi-passive. Then, the corresponding finite-time quasi-passivity-based adaptive stabilization is studied. Finally, a practical example is presented to illustrate the effectiveness of our method.

This paper studies the problem of obstacle avoidance and trajectory tracking for a class of uncertain nonlinear systems with unmeasured states and actuator faults. The main difficulty is that actuator faults may cause significant transient tracking errors, which might lead to collisions. To overcome this difficulty, an adaptive observer is developed to estimate system states and compensate for actuator faults. Additionally, the integral-multiplicative Barrier Lyapunov function (BLF) is integrated into the backstepping procedure to overcome the dynamics mismatching problem of the existing SUM-type BLF. The proposed adaptive scheme can avoid collisions in a multi-obstacle environment even if the actuator faults occur, and all the signals are uniformly ultimately bounded. Simulation results demonstrate the effectiveness of this approach.

This paper investigates the event-triggered $��{�l�}_{�2�}�-�{�l�}_{�\infty �}�$ filtering problem for discrete-time switched systems subject to denial-of-service attacks. To address the mismatch between the filter modes and the system modes induced by the event-triggered strategy, the mode-dependent average dwell time switching law is introduced to guarantee the global uniform exponential stability of the switched filtering error system with the $��{�l�}_{�2�}�-�{�l�}_{�\infty �}�$ performance. Unlike traditional average dwell time, which relies on a fixed dwell time threshold, mode-dependent average dwell time dynamically assigns mode-dependent dwell time thresholds, significantly improving flexibility in stability analysis and filter design during asynchronous intervals. Furthermore, collaborative design methods for the filter and event-triggered parameters under denial-of-service attacks are provided. Finally, the feasibility and applicability of the proposed approach are demonstrated through a numerical example and the model of a boost converter controlled by pulse-width modulation.