International Journal of Control Automation and Systems最新文献

This paper introduces a new dynamical model for a continuous snake-like robot and a controller yielding slithering motion on a smooth curved surface. Smooth curve models are common tools in studies on snake-like robots, however, the application of those models is limited to cases without sideslips. Our new model can deal with locomotion with sideslips on curved surfaces. Moreover, the numerical simulation of climbing up the surface of a cylinder based on our model reveals the important role of the tangential friction of the body, which was underestimated by previous studies. The result illuminates the trade-off relation between the energy efficiency and the reachability of the snake-like robots.

This paper investigates the finite-time stabilization problem of fractional-order impulsive switched systems with saturated control input and matched disturbance. Saturated control input exists in the continuous time intervals as well as at the impulsive instants. By using the average dwell time approach, the Lyapunov stability theory and the binomial theorem, sufficient conditions are proposed to guarantee finite-time stability of the closed-loop system. Meanwhile, the controller gains can be got via solving linear matrix inequalities. In addition, the biggest attraction domain is obtained by solving the proposed optimization problem. Finally, numerical examples are provided to illustrate the effectiveness of the designed controller.

In this paper, an adaptive back-stepping control scheme based on the command filter is proposed for the servo system with current constraints and non-symmetric dead zone. First, a novel system transformation scheme is designed to transform the servo system with current constraints into the equivalent “unconstrained”. A security boundary is incorporated into the designed strategy to restrict the activation state of the constraint mechanism. Second, the asymmetric dead zone nonlinearities can be represented into a parameterized form by using a continuous piecewise linear neural network (CPLNN). Moreover, an adaptive law with guaranteed convergence is used to online update the CPLNN weights so as to derive the dead zone characteristic parameters and then compensate for the asymmetric dead zone. Then, the command filter is introduced into the back-stepping control strategy to avoid the complexity explosion. The stability analysis of the closed-loop system is proved by the Lyapunov stability theory. Finally, the effectiveness and feasibility of the proposed control scheme are validated through the real-time experiments on a permanent magnet synchronous motor (PMSM) platform.

This paper mainly investigates the consensus problem of heterogeneous multi-agent systems (HMASs) consisting of second-order linear and second-order nonlinear agents under input saturation. First, the consensus control protocols for HMASs in the leaderless case and the leader-following case are designed under undirected connected topology respectively, where there is a static leader under the leader-following network. Then, based on the knowledge of graph theory and Lyapunov stability theory, it is proved that HMASs can finally reach consensus if sufficient conditions are satisfied. Eventually, the effectiveness of the above theory is further illustrated by simulation examples.

In the realm of infrared (IR) small target detection, pinpointing blurry and low-contrast targets accurately is immensely challenging due to the intricate features of IR images. To tackle this, we introduce CSI-Net, a novel network architecture merging CNN and swin transformer. CSI-Net features a hybrid encoder design, blending encoder-decoder layout of UNet with swin transformer’s parallel execution alongside CNN. This amalgamation enables the network to capture local features and long-distance dependencies, enhancing its ability to accurately identify small targets. Leveraging hierarchical features of swin transformer, CSI-Net adeptly grasps contextual information crucial for small target detection. Moreover, CSI-Net employs full-scale skip connections over encoder-decoder and decoder-decoder, integrating multiscale CNN and swin transformer features to improve gradient propagation. Experimental results validate superiority of proposed method over traditional CNN and Transformer methods. At NUAA-SIRST, metrics like mIoU (0.7483), detection probability (0.9734), and false alarm rates (0.101 × 10⁻⁵) demonstrate significant improvement. Similarly, at NUDT-SIRST, values like mIoU (0.8887), detection probability (0.9894), and false alarm rates (0.431 × 10⁻⁵) show notable enhancement. The performance of network scales with dataset size, and its robustness is affirmed by the area under the ROC curve (AUC). Additionally, an ablation study validates the efficacy of hybrid encoder. Varying the presence of the parallel swin transformer module (PSM) reveals that its application enhances small target detection performance. The comprehensive evaluation shows that the swin transformer-enhanced UNet architecture effectively tackles the challenges of IR small target detection.

This paper investigates state estimation and system consensus control for multiagent systems with nonlinear function under communication topology. A novel weighted fixed-time observer is designed to estimate the system states. The observer designed in this paper takes the output errors of its own agent into account in weight distribution, and the agent state should not be known. A Lyapunov function is designed to make the estimation error globally fast fixed-time stable. This observer-based feedback controller is explored for keeping the consensus error system globally fast fixed-time stable. At last, two examples are considered in the simulation section to illustrate the effectiveness of the weighted fixed-time observer as well as controller.

Under the general unbalanced directed communication graphs, distributed fixed-time optimization problem is studied for multiple mechanical systems modeled by Euler-Lagrange equations. Distributed controllers have been developed to achieve the optimal position of each agent within a fixed time by integrating distributed fixed-time estimator techniques and a fixed-time control design in a cohesive manner. The effectiveness of the proposed control protocol is also illustrated by a numerical simulation.

This paper presents the design of active harmonic current compensator (AHCC) to mitigate the current harmonics generated by supply side for an induction furnace application. Induction furnaces have nonlinear and time-varying properties, resulting in harmonics and voltage/current imbalances. AHCC are high-speed compensators that enhance the performance of induction furnaces and solve power quality issues. The proposed system is designed with modified higher order sliding control (MHOSC) algorithm and extended form of reactive power theory to generate a three-phase reference compensating current. The control method examines the sliding surface parameter uncertainties in order to obtain a controlled direct current (DC) link current when using nonlinear converters. The proposed work compares the performance of proportional integral (PI) tuned sliding mode controllers with emotional tuned intelligent controllers (ETIC). The compensated current reference signal is used to provide switching pulses for AHCC. A major advantage of MHOSC is its ability to endure external disruptions and unpredicted parameter changes, which improves reference current tracking without introducing undesirable oscillations (chattering). Implementation of the proposed control algorithm is validated in MATLAB / Simulink demonstrating that the designed AHCC compensates the harmonic current to an acceptable level (total harmonic distortion of source current is 1.54%) satisfying IEEE 519-2014 standard.

With the growing prevalence of technologies such as drones, mobile robots, and autonomous vehicle fleets, multi-agent collaborative control has emerged as a significant area of research. This article focuses on distributed observer-based formation control for multi-agent systems with a leader-follower structure, utilizing edge-event triggered mechanisms. Unlike traditional formation controls that depend on complete access to the leader’s velocity, this method requires only a select few followers to have access to the time-varying velocity information of the leader. A distributed velocity observer was developed through an edge-event triggered mechanism to reduce unnecessary data transmissions and conserve energy. Additionally, a bearing-based formation controller built on input-to-state stability theory was introduced to effectively manage formation tracking and execute scaling maneuvers. Numerical simulations demonstrate the effectiveness of the proposed methods and highlight their advantages over traditional node-based event-triggered strategies.

Stereotaxic surgeries for distributed implantation of microelectrodes into rat brains are vital for establishing brain-computer interfaces in neuroscience research. Minimally invasive craniotomy and microelectrode implantation are two related major surgical tasks requiring high accuracy and safety. In the literature, existing robotic systems are generally developed for a separate surgical task. However, the accuracy of drilling craniotomy performed first can directly affect the implantation outcomes later. Thus, we develop a function-integrated neurosurgical robot capable of completing multiple cranial drillings and distributed implantation of microelectrodes. A drilling module with bio-impedance feedback and an implantation module with adaptive grippers are integrated with a five-axis motion platform. Surgical planning methods based on Bezier curves and potential informed Bi-RRT, as well as kinematic relationships of the robotic system, are developed to guide the robot with obstacle avoidance in the surgical scene. The surgical path simulation is conducted to validate the effectiveness of the planning method. The experiments involving two surgical tasks and a repeated test at different implantation depths jointly demonstrate that this prototypical robot can perform the surgery with high accuracy and safety, indicating great potential in reducing the workload of surgeons and minimizing surgical failure rates.