Search Results (58)

This paper proposes a control method that combines a fractional-order sliding mode observer and a cooperative control strategy to address the problem of path-following for underactuated autonomous underwater vehicles (AUVs) in complex marine environments. First, a fractional-order sliding mode observer is designed, combining fractional calculus and double-power convergence laws to enhance the estimation accuracy of high-frequency disturbances. An adaptive gain mechanism is introduced to avoid dependence on the upper bound of disturbances. Second, a formation cooperative control strategy based on path parameter coordination is proposed. By setting independent reference points for each AUV and exchanging path parameters, formation consistency is achieved with low communication overhead. For the followers’ speed control problem, an error-based expected speed adjustment mechanism is introduced, and a hyperbolic tangent function is used to replace the traditional arctangent function to improve the response speed of the system. Numerical simulation results show that this control method performs well in terms of path-following accuracy, formation maintenance capability, and disturbance suppression, verifying its effectiveness and robustness in complex marine environments. Full article

Underactuated systems, such as the Cart–Pole and Acrobot, pose significant control challenges due to their inherent nonlinearity and limited actuation. Traditional control methods often struggle to achieve stable and optimal performance in these complex scenarios. This paper presents a novel stable reinforcement learning (RL) approach for underactuated systems, integrating advanced exploration–exploitation mechanisms and a refined policy optimization framework to address instability issues in RL-based control. The proposed method is validated through extensive experiments on two benchmark underactuated systems: the Cart–Pole and Acrobot. In the Cart–Pole task, the method achieves long-term balance with high stability, outperforming traditional RL algorithms such as the Proximal Policy Optimization (PPO) in average episode length and robustness to environmental disturbances. For the Acrobot, the approach enables reliable swing-up and near-vertical stabilization but cannot achieve sustained balance control beyond short time intervals due to residual dynamics and control limitations. A key contribution is the development of a hybrid PPO–sliding mode control strategy that enhances learning efficiency and stabilities for underactuated systems. Full article

This paper presents a composite disturbance-tolerant control framework for quadrotor unmanned aerial vehicles (UAVs). By constructing an enhanced dynamic model that incorporates parameter uncertainties, external disturbances, and actuator faults and considering the inherent underactuated and highly coupled characteristics of the UAV, a novel robust adaptive sliding mode controller (RASMC) is designed. The controller adopts a hierarchical adaptive mechanism and utilizes a dual-loop composite adaptive law to achieve the online estimation of system parameters and fault information. Using the Lyapunov method, the asymptotic stability of the closed-loop system is rigorously proven. Simulation results demonstrate that, under the combined effects of external disturbances and actuator faults, the RASMC effectively suppresses position errors (<0.05 m) and attitude errors (<0.02 radians), significantly outperforming traditional ADRC and LQR control methods. Further analysis shows that the proposed adaptive law enables the precise online estimation of aerodynamic coefficients and disturbance boundaries during actual flights, with estimation errors controlled within ±10%. Moreover, compared to ADRC and LQR, RASMC reduces the settling time by more than 50% and the tracking overshoot by over 70% while using the ($tanh(·)$) approximation to eliminate chattering. Prototype experiments validate the fact that the method achieves centimeter-level trajectory tracking under real uncertainties, demonstrating the superior performance and robustness of the control framework in complex flight missions. 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

Simulating low- or zero-gravity environments on the ground is an important technology in the field of space exploration. Suspension-based gravity offloading (SGO) systems are commonly used ground-based platforms for simulating space environments. Nevertheless, the control of SGO systems presents significant challenges due to external disturbances and stringent response time requirements. This study proposes a predefined-time (PdT) observer-based PdT control framework to address the SGO system control problem. To begin, a pneumatic artificial muscle-based active unloading mechanism is introduced to address the inherent underactuation problem in the SGO system. Thereafter, a PdT disturbance observer is introduced to estimate the external disturbances acting on the SGO system. Subsequently, a type of PdT controller is investigated for the SGO system. The system, including the PdT disturbance observer and the PdT controller, is proven to be PdT stable in the Lyapunov sense. Finally, sufficient numerical simulations and physical experiments are conducted to verify the superiority and effectiveness of the proposed control method. Full article

In this paper, we study $H_{\infty }$ control for systems with explicit mechanical constraints and a lack of state information, such as walking robots. This paper proposes an $H_{\infty }$ control design scheme based on solving an optimization problem with linear matrix inequality constraints. Our method is based on the orthogonal decomposition of the state variables and the use of two linear controllers and a Luenberger observer, tuned to achieve the desired properties of the closed-loop system. The method takes into account static linear additive disturbance, which appears due to the uncertainties associated with the mechanical constraints. We propose a dynamics linearization procedure for systems with mechanical constraints, taking into account the inevitable lack of information about the environment; this procedure allows a nonlinear system to be transformed into a form suitable for the application of the proposed control design method. The method is tested on a constrained underactuated three-link robot and a flat quadruped robot, showing the desired behavior in both cases. Full article

Traditional multirotor UAVs (unmanned aerial vehicles) are inherently underactuated, with coupled position and attitude control, which limits their maneuverability in specific applications. This paper presents a fully actuated quadrotor design based on a swashplateless rotor mechanism. Unlike existing fully actuated UAV designs that rely on servo-driven tilt mechanisms, this approach minimizes additional weight and simplifies the structure, resulting in a more maintainable system. The design, modeling, and control strategies for the quadrotor are presented. Furthermore, we propose a decoupled control method to address the need for both fully actuated and underactuated modes. The control architecture employs parallel attitude and position control structures and decouples the two subsystems using a nonlinear dynamic inversion (NDI) method. A compensation module is introduced to address the constraints imposed by the maximum rotor deflection angle and the corresponding feasible force set. This compensation module actively adjusts the attitude to mitigate the saturation of the required thrust, effectively overcoming the impact of rotor deflection angle limitations on trajectory tracking performance. The approach facilitates seamless switching between fully actuated and underactuated modes, enhancing the system’s flexibility and robustness. Simulation and flight experiments demonstrate the effectiveness and performance of the proposed design. Full article

This paper proposes a dynamic event-triggered adaptive backstepping control for underactuated autonomous underwater vehicle systems (AUVs) with input saturation. The proposed method ensures the system’s stability by introducing a new auxiliary signal system to compensate for the input saturation. Firstly, the underactuated AUVs is separated into the underactuated part and the actuated part, and then the dynamic auxiliary signal system is introduced. A transformation is used to combine the actuated part with the auxiliary signal system. The controller is designed using the adaptive backstepping method, and a dynamic event-triggering mechanism is constructed to obtain the event-triggering controller. A strict theoretical analysis is provided to avoid the Zeno phenomenon. Finally, the effectiveness of the dynamic event-triggered adaptive backstepping controller is verified by simulation. Full article

This paper addresses the robust control problem for under-actuated mechanical systems subject to uncertainties. The key challenge lies in achieving precise control with insufficient degrees of freedom while maintaining robustness against system uncertainties. We propose a novel control framework that characterizes bounded, time-varying uncertainties through fuzzy set theory, leading to a fuzzy dynamical system formulation. The main contributions are threefold: (1) the development of a deterministic robust controller that eschews traditional IF-THEN rules while guaranteeing system stability through a Lyapunov–Minimax analysis; (2) the formulation of a performance optimization scheme that minimizes both fuzzy system average performance and control costs, with proven existence and uniqueness of the analytical solution; and (3) the establishment of stability conditions using the Lyapunov theory for time-varying systems with bounded uncertainties. The theoretical framework is validated through both numerical simulations and experimental implementation on a linear motor-driven inverted pendulum system. The experimental results demonstrate significant performance improvements over conventional approaches: the optimal robust controller achieves 34.89% and 29.20% reductions in cart position and pendulum angle errors, respectively, from the initial conditions. A comparative analysis with traditional PD control shows a reduction in steady-state errors from 0.00318 m to 0.00057 m for the cart position and from 0.01117 rad to 0.00055 rad for the pendulum angle, validating the effectiveness of the proposed methodology. Full article

Overhead cranes are widely used for transportation in factories. They move slowly by manual operation to prevent the payload from swinging sharply or colliding with sudden obstacles. To address these issues and enhance work efficiency, this paper proposes a couple anti-swing obstacle avoidance control method for 5-DOF overhead cranes. Time polynomial fitting is employed for trajectory planning to achieve obstacle avoidance. To achieve anti-swing of the payloads, a coupled variable incorporating both actuated and underactuated states is defined, alongside a boundary for dynamic performance. Finally, MATLAB simulation and hardware experiments are carried out to verify the reliability and compared with some existing control methods. Full article

In this paper, we address the modeling, simulation, and control of a rotary inverted pendulum (RIP). The RIP model assembled via the MATLAB (Matlab 2021a)^®/Simulink (Simulink 10.3) Simscape (Simscape 7.3)™ environment demonstrates a high degree of fidelity in its capacity to capture the dynamic characteristics of an actual system, including nonlinear friction. The mathematical model of the RIP is obtained via the Euler–Lagrange approach, and a parameter identification procedure is carried out over the Simscape model for the purpose of validating the mathematical model. The usefulness of the proposed Simscape model is demonstrated by the implementation of a variety of control strategies, including linear controllers as the linear quadratic regulator (LQR), proportional–integral–derivative (PID) and model predictive control (MPC), nonlinear controllers such as feedback linearization (FL) and sliding mode control (SMC), and artificial intelligence (AI)-based controllers such as FL with adaptive neural network compensation (FL-ANC) and reinforcement learning (RL). A design methodology that integrates RL with other control techniques is proposed. Following the proposed methodology, a FL-RL and a proportional–derivative control with RL (PD-RL) are implemented as strategies to achieve stabilization of the RIP. The swing-up control is incorporated into all controllers. The visual environment provided by Simscape facilitates a better comprehension and understanding of the RIP behavior. A comprehensive analysis of the performance of each control strategy is conducted, revealing that AI-based controllers demonstrate superior performance compared to linear and nonlinear controllers. In addition, the FL-RL and PD-RL controllers exhibit improved performance with respect to the FL-ANC and RL controllers when subjected to external disturbance. Full article

Planar underactuated mechanical systems have been a popular research issue in the area of mechanical systems and nonlinear control. This paper reviews the current research status of control methods for a class of planar underactuated manipulator (PUM) systems containing a single passive joint. Firstly, the general dynamics model and kinematics model of the PUM are given, and its control characteristics are introduced; secondly, according to the distribution position characteristics of the passive joints, the PUM is classified into the passive first joint system, the passive last joint system, and the passive intermediate joint system, and the analysis and discussion are carried out in respect to the existing intelligent control methods. Finally, in response to the above discussion, we provide a brief theoretical analysis and summarize the challenges faced by PUM, i.e., uncertainty and robustness of the system, unified control methods and research on underactuated systems with uncontrollable multi-passive joints; at the same time, the practical applications have certain limitations that need to be implemented subsequently, i.e., anti-jamming, multi-planar underactuated robotic arm co-control and spatial underactuated robotic arm system development. Aiming at the above challenges and problems in the control of PUM systems, we elaborate on them in points, and put forward the research directions and related ideas for future work, taking into account the contributions of the current work. Full article

Generally, nonlinear systems have dynamic uncertainties, and under certain conditions, the systems exhibit different chaos intensities. Therefore, it is an important consideration for designers to realize the suppression and enhancement of chaos intensity under nonlinear factors according to the actual situation, but there are few research results on this problem. To investigate the dynamic performance and chaotic intensity of a nonlinear mechanism, a planar closed-chain under-actuated mechanism, which has not been extensively studied before, is taken as an example. It is worth noting that a small change in the parameters of a nonlinear system will cause a large change in the motion state of the system and even the mutual transformation between chaotic phenomena and periodic phenomena. To solve this problem, uniformity is used to evaluate the chaos intensity of the system. Finally, based on uniformity, the particle swarm optimization algorithm successfully achieves the suppression and enhancement of the chaos intensity of the closed-chain under-actuated five-bar mechanism by optimizing its linkage length and driving speed, and the results are verified by the experimental platform. Full article

This paper presents a controller design to track speed, position, and torque trajectories for a permanent magnet synchronous motor (PMSM). This scheme is based on the interconnection and damping assignment passivity-based control (IDA-PBC) technique recently proposed to solve the tracking control problem for mechanical underactuated systems. The proposed approach regulates the dynamics of the tracking system error at the origin, assuming the realizable trajectories preserve the motor’s port-controlled Hamiltonian structure. The importance of the contribution is two-fold: First, from the theoretical perspective, the trajectory tracking control problem is solved with proved stability properties, a topic that has not been deeply studied with the IDA-PBC methodology design. Second, from the practical point of view, the proposed control scheme exhibits a simple structure for practical implementation and strong robustness properties with respect to parametric uncertainties. The contribution is evaluated under both numerical and experimental environments considering a speed profile that demands the achievement of high dynamic performances. Full article

This article proposes a comprehensive stable control strategy for the planar multi-link underactuated manipulator (PMLUM), considering several uncertainties. According to the nilpotent approximation property, the control procedure is split into two stages. In the first stage of control, we postulate the idea of model degradation, reducing the PMLUM to a planar virtual Pendubot (PVP). This occurs by controlling the active link (AL) to a specific desired position and the passive link (PL) moves along with it. When the AL moves to the desired position, the second phase of control is entered. Meanwhile, all ALs are regarded as a whole, so the PMLUM can be regarded as a mechanical arm with 2-DOF. In the second stage of control, due to the nilpotent approximation feature of the PVP, the PVP is guided to the desired angle using the iterative steering technique. Simulation experiments are carried out on active–active–passive (AAP) and active–active–active–passive (AAAP) systems under major uncertainties, which contain initial velocity and torque disturbances. The final results validate the effectiveness of the method proposed. Full article