Search Results (70)

This paper presents a three-dimensional robust spatiotemporal cooperative guidance law for unmanned aerial vehicles (UAVs) to track a dynamic target under jointly strongly connected topologies, even when some UAVs malfunction. To resolve the infinite gain challenge in existing prescribed-time cooperative guidance laws, a novel bounded-gain prescribed-time stability criterion was formulated. This criterion allows the convergence time of the guidance law to be prescribed arbitrarily without any convergence performance trade-off. Firstly, new prescribed-time disturbance observers are designed to achieve accurate estimations of the target acceleration within a prescribed time regardless of initial conditions. Then, by leveraging a distributed convex hull observer, a tangential acceleration command is proposed to drive arrival times toward a common convex combination within a prescribed time under jointly strongly connected topologies, remaining effective even when partial UAVs fail. Moreover, by utilizing a prescribed-time nonsingular sliding mode control method, normal acceleration commands are developed to guarantee that the line-of-sight angles constraints can be satisfied within a prescribed time. Finally, numerical simulations validate the effectiveness of the proposed guidance law. Full article

In this paper, a sliding-mode control strategy incorporating prescribed features was systematically designed, resolving the dual challenges of trajectory tracking precision maintenance and disturbance attenuation for an AUV subjected to dynamic model inaccuracies and disturbances. To neutralize the impact of parametric uncertainties and environmental disturbances on the controlled plant, an adaptive finite-time sliding-mode disturbance observer (AFTSMDO), the upper bound of perturbations was not required for the proposed observer. Subsequently, by embedding error transformations and prescribed performance functions, we designed a novel sliding-mode surface. This surface ensured that tracking errors and their derivatives converge to specified regions within predefined temporal bounds, irrespective of initial configurations. This overcomes the longstanding limitations of traditional prescribed performance control methods and contributes to enhancing system performance. Finally, we conducted comparative simulation experiments with existing sliding-mode control methods to prove the practical viability and comparative advantage of the synthesized control methodology. Full article

This study proposes an event-triggered fault-tolerant active disturbance rejection control (ADRC) method for variable-load quadrotors with prescribed performance. The quadrotor, as a nonlinear and underactuated system, faces challenges such as payload variations, actuator faults, and external disturbances, which degrade trajectory tracking accuracy and stability. The proposed approach integrates a cascaded ADRC framework, decoupling the system into position and velocity subsystems, each equipped with extended state observers (ESOs) for real-time disturbance estimation and compensation. To enhance robustness, prescribed performance functions dynamically constrain tracking errors within predefined bounds, while event-triggered mechanisms reduce computational load through condition-based updates of control signals. Additionally, a particle swarm optimization (PSO) algorithm is employed for online parameter tuning, improving adaptability. Theoretical analysis confirms the system stability, and simulation results demonstrate the controller effectiveness in handling actuator faults and variable payloads, ensuring accurate trajectory tracking and reduced resource consumption. The method offers a promising solution for robust and efficient quadrotor control in complex environments. Full article

This research proposes a fractional-order adaptive neural control scheme using an optimized backstepping (OB) approach to address strict-feedback nonlinear systems with uncertain control directions and predefined performance requirements. The OB framework integrates both fractional-order virtual and actual controllers to achieve global optimization, while a Nussbaum-type function is introduced to handle unknown control paths. To ensure convergence to desired accuracy within a prescribed time, a fractional-order dynamic-switching mechanism and a quartic-barrier Lyapunov function are employed. An input-to-state practically stable (ISpS) auxiliary signal is designed to mitigate unmodeled dynamics, leveraging classical lemmas adapted to fractional-order systems. The study further investigates a decentralized control scenario for large-scale stochastic nonlinear systems with uncertain dynamics, undefined control directions, and unmeasurable states. Fuzzy logic systems are employed to approximate unknown nonlinearities, while a fuzzy-phase observer is designed to estimate inaccessible states. The use of Nussbaum-type functions in decentralized architectures addresses uncertainties in control directions. A key novelty of this work lies in the combination of fractional-order adaptive control, fuzzy logic estimation, and Nussbaum-based decentralized backstepping to guarantee that all closed-loop signals remain bounded in probability. The proposed method ensures that system outputs converge to a small neighborhood around the origin, even under stochastic disturbances. The simulation results confirm the effectiveness and robustness of the proposed control strategy. Full article

This work focuses on fixed-time synchronized trajectory tracking control for unmanned airships subject to time-varying error constraints and unknown disturbances. First, to guarantee strict adherence to prescribed performance bounds, an error transformation function (ETF) is integrated into the control algorithm, which can ensure all tracking errors remain within specified constraints throughout the convergence process. Then, a Norm-Normalized sign (NNS) function is incorporated to develop the control scheme, guaranteeing simultaneous convergence of all tracking error components. Additionally, a novel fixed-time synchronized disturbance observer (FTSDO) is constructed and implemented to achieve precise disturbance estimation while ensuring synchronous convergence of the estimation errors. Finally, the developed control strategy is analytically verified to guarantee fixed-time synchronized stability (FTSS). To assess its performance, multiple simulations are executed. The results clearly demonstrate the proposed control scheme enables the airship to track the prescribed trajectory precisely in fixed time, and the convergence of all tracking error components is achieved synchronously. Full article

A prescribed performance neuro-adaptive control scheme is proposed for a single-link flexible-joint robotic manipulator with unknown deadzone and actuator faults. A new smooth deadzone inverse model is constructed to offset the adverse effect caused by the input deadzone in the actuator of flexible-joint manipulators. The control law is developed by coordinating prescribed performance control with a backstepping technique to ensure transient/steady-state performance, while adaptive neural networks are employed for uncertainty approximation. The tracking error is always restricted within the prescribed bound during the control process, and it ultimately converges to the small neighborhood of origin. All signals in the closed-loop flexible-joint robotic manipulator system are proved to be uniformly bounded. Simulation results are provided to demonstrate the efficiency of the prescribed performance adaptive neural network backstepping control scheme. Full article

This paper proposes a modular control framework for high-order nonlinear multi-agent systems (MASs) to achieve distributed finite-time formation tracking with a prescribed performance. The design integrates two modules to address uncertainties and safety constraints simultaneously. Module I—Prescribed Performance-Based Trajectory Generation: A virtual signal generator constructs collision/connectivity-aware reference trajectories by encoding time-varying performance bounds into formation errors. It ensures network rigidity and optimal formation convergence through dynamic error transformation. Module II—Anti-disturbance Tracking Control: A finite-time extended state observer (FTESO) estimates and compensates for uncertainties within a finite time, while a time-varying surface controller drives tracking errors into predefined performance funnels. This module guarantees rapid error convergence without violating the transient constraints from Module I. The simulations verified the accelerated formation reconfiguration under disturbances, and thus, demonstrated improved robustness and convergence over asymptotic approaches. The framework offers a systematic solution for safety-critical MAS coordination with heterogeneous high-order dynamics. Full article

This paper investigates an adaptive fault-tolerant control strategy for the Twin Otter aircraft, aimed at addressing critical challenges arising from system uncertainties and actuator faults. A global prescribed performance function is employed to ensure pre-determined transient and steady-state tracking performance under uncertainties and faults. Differing from existing prescribed performance controllers, the proposed approach is characterized by (1) no limitation on the initial tracking error; (2) no requirement for tracking error normalization; and (3) incorporation of an improved monitoring function. Specifically, this novel monitoring function dynamically adjusts prescribed error bounds based on real-time fault information, thus enhancing flexibility and robustness. Furthermore, fixed-time convergence of the tracking error is rigorously guaranteed, significantly improving system reliability and safety. Although the simplified Twin Otter aircraft model analyzed herein is a second-order parametric strict-feedback system, the theoretical framework extends naturally to higher-order strict-feedback systems. The effectiveness and advantages of the proposed method are validated through theoretical analysis and numerical simulations on a Twin Otter aircraft system with time-varying parameters and actuator faults. Full article

Flexible-joint manipulators have a lightweight nature, compact structure, and high flexibility, making them widely applicable in industrial manufacturing, biomedical instruments, and aerospace fields. However, the inherent flexibility of single-link flexible-joint manipulators (SLFJMs) poses substantial control challenges. Compared to traditional control algorithms, prescribed performance control (PPC) algorithms provide superior transient response and steady-state performance by defining a prescribed performance function. However, existing PPC algorithms are limited to a specific range of system initial states, which reduces the joint manipulator’s operational workspace and weakens the robustness of the control algorithm. To address this issue, this study proposes a prescribed performance bounded-H_∞ fault-tolerant controller for SLFJMs. By designing an improved tangent-type barrier Lyapunov function (BLF), a prescribed performance controller that is independent of the initial state of the SLFJM is developed. An input control function (ICF) is employed to mitigate the impulse response of the control input, ensuring a smooth transition from zero. Furthermore, the improved tangent-type BLF enables the tracking error to rapidly converge to a small neighborhood of zero. Finally, a stabilization control simulation experiment is conducted; the results validate the effectiveness of the proposed prescribed performance bounded-H_∞ controller. Full article

This brief tackles the predefined-time attitude tracking problem with guaranteed performance for rigid spacecraft subject to uncertain inertia, external disturbances, and actuator partial failure. Firstly, a nonlinear prescribed performance function (NPPF) is constructed, and a non-singular predefined-time terminal sliding mode (NPTSM) surface integrating with the NPPF is introduced. Secondly, adaptive non-singular predefined-time guaranteed performance control (ANPTGPC) is designed to tackle the robust attitude tracking problem of rigid spacecraft with predefined-time stability. It is proven that attitude tracking errors can be constrained in the preset tracking performance bound within predefined time. They tend to a small region centered around zero in predefined time and then converge to zero asymptotically. Features of the proposed ANPTGPC include an absence of a model, nonsingularity, predefined-time stability with performance quantified, fast transience, and high steady-state accuracy. Numerical simulation results validate the effectiveness and improved performance of the proposed approach. Full article

This article proposes a prescribed-time formation tracking control scheme for USVs with prescribed performance constraints to address the issue of multiple underactuated USV formation tracking control with external environmental disturbances and input saturation. Initially, a prescribed-time extended state observer was constructed, capable of promptly estimating and compensating for speed and external disturbances within a certain timeframe. Additionally, a unique performance function was developed, enabling the performance function to converge to a predetermined accuracy within a specified time, while allowing for flexible adjustment of the performance constraint shape by parameter modification. Furthermore, a prescribed-time formation control algorithm was developed by combining graph theory and dynamic surface control, enabling the formation error to converge within preset performance constraints at a specified period of $\mathrm{T}=10 \mathrm{s}$. It was proved that all signals in the closed-loop system are uniform, ultimately bounded by Lyapunov stability theory and the formation tracking errors display prescribed-time stability. Finally, the efficacy and superiority of the designed control scheme were evaluated by constructing numerical simulations. Full article

In manufacturing, the position tracking accuracy and stability of Permanent Magnet Synchronous Motors are often challenged by uncertainties, especially in complex environments. Existing control methods struggle to balance fast response with high-precision tracking. To address this, we propose a Prescribed Performance Global Non-Singular Fast Terminal Sliding Mode Control (PPGNFTSMC) method using a linear extended state observer (LESO). A smooth and bounded prescribed performance function is designed to ensure finite-time convergence while satisfying performance requirements such as overshoot and settling time. Based on this function, the system error is reconstructed to align the system response with predefined specifications. The reconstructed error is then used to design a global non-singular fast terminal sliding mode surface. A LESO is employed for real-time disturbance estimation, and the disturbance estimates, along with the sliding mode surface, are used to derive the control law for the position–speed integrated controller. Experimental results show that the proposed method outperforms the comparison methods in transient response, tracking accuracy, and robustness across various signal types. Full article

This paper proposes a prescribed performance tracking control scheme for a category of nonlinear stochastic time-delay systems with input saturation and state asymmetric time-varying constraints. First, to solve the non-differentiable problem caused by input saturation, a smooth nonlinear function was utilized to approximate the saturation function. A nonlinear mapping technique was employed to transform the constrained problem into a bounded convergence problem. The time-delay problem was then solved by constructing the corresponding Lyapunov–Krasovskii function. The error feedback controller was constructed by combining the backstepping technique, the dynamic surface technique, the neural network approximation technique, and the adaptive control method. Based on stochastic mean-square stability theory, all signals in the closed-loop system are proven to be bounded under the designed control scheme. Also, this scheme ensures that the system states always stay within the constraint range, and the tracking error meets the prescribed performance constraint. Finally, the feasibility and superiority of the proposed control scheme were validated through simulation. Full article

This paper addresses the time-optimal control problem for a harmonic oscillator characterized by a time-dependent frequency. The primary objective is to determine the minimal time required to transition the system from an initial state, defined by a given position and velocity, to a specified final state, while ensuring that the frequency remains within prescribed bounds. The key challenge lies in identifying the optimal switching times between two available frequencies to meet all boundary conditions efficiently. By examining various boundary scenarios, constructing the reachable set of all admissible trajectories, and employing both analytical techniques and control theory, we develop a robust solution strategy. This work holds particular relevance for practical applications demanding rapid state transitions, such as mechanical vibration control and signal processing, where achieving time-optimal performance is critical. Furthermore, the methods presented are adaptable to a wide range of systems facing similar constraints, providing a versatile and effective framework for time-optimal control. Full article

This paper proposes the fixed-time prescribed performance optimal consensus control method for stochastic nonlinear multi-agent systems with sensor faults. The consensus error converges to the prescribed performance bounds in fixed-time by an improved performance function and coordinate transformation. Due to the unknown faults in sensors, the system states cannot be gained correctly; therefore, an adaptive compensation strategy is constructed based on the approximation capabilities of neural networks to solve the negative impact of sensor failures. The reinforcement-learning-based backstepping method is proposed to realize the optimal control of the system. Utilizing Lyapunov stability theory, it is shown that the designed controller enables the consensus error to converge to the prescribed performance bounds in fixed time and that all signals in the closed-loop system are bounded in probability. Finally, the simulation results prove the effectiveness of the proposed method. Full article