Multiple mobile robot systems, as a dynamic type of the Internet of Things (IoT), have been gaining widespread attention. In this article, the prescribed-time (PT) formation control of nonholonomic mobile robots (NMRs) with uncertainties is investigated under the leader-follower architecture. First, the nonholonomic constraints of the mobile robots are sufficiently considered, and a transformation method is presented to convert the original nonholonomic system into an easy-to-handle Euler-Lagrange (EL) system. In addition, fuzzy logic systems (FLSs) and adaptive techniques are employed to deal with uncertainties, such as the damping matrix, so that the negative effects of approximation errors can be eliminated. By applying the sliding mode control (SMC) technique and PT stability theory, a sliding mode protocol is proposed to ensure that all states of the mobile robots can be driven onto the sliding surface and the formation errors converge within the prescribed time. Finally, simulations and experiments are conducted to demonstrate the effectiveness of the proposed method.

This paper investigates the predefined-time (PdT) formation control problem for heterogeneous wheeled mobile robots (WMRs) with complex nonlinear terms. To address the challenges arising from system heterogeneity and distributed coordination, a reference-tracking control framework is proposed. The first layer is a reference signal generation layer, where PdT formation trajectories are generated by signal generators, with local observers embedded in each agent to estimate the leader’s state when direct access is unavailable. The second layer is an agents tracking layer, where each WMR follows its assigned reference trajectories. By coordinating these two layers, the proposed framework enables distributed formation control within a predefined time. To achieve PdT tracking, a sliding mode control strategy enhanced with fuzzy logic control is developed in the tracking layer. Lyapunov-based analysis is conducted for both layers to ensure PdT stability and provide explicit convergence-time guarantees. Simulation results are presented to validate the theoretical analysis and demonstrate the effectiveness of the proposed method.

This article investigates the prescribed-time fault-tolerant formation (PTFTF) control problem for heterogeneous switched nonlinear multiagent systems (HSNMASs) with actuator faults. In particular, the system under consideration exhibits both heterogeneity and switching dynamics, and operates over a directed topology. A novel PTFTF protocol that includes two adaptive laws and an auxiliary system is proposed by introducing a time-varying function. It is noteworthy that the constructed auxiliary system can effectively address the heterogeneity and switching characteristics of the system. Fuzzy logic systems (FLSs) are utilized to approximate potentially unknown nonlinear functions that are not required to satisfy the specific growth conditions. Notably, the adaptive law, newly designed as a key part of the protocol, eliminates the adverse effects of fuzzy approximation errors, ensuring that formation errors converge to zero within any given time. Finally, the effectiveness of the proposed protocol is demonstrated through both numerical and comparative simulations.

This article investigates a distributed finite-horizon optimal leader-follower consensus for discrete-time multi-agent systems with prescribed performance. Each agent has a limited communication range. First, to maintain the topology connectivity and satisfy performance requirements, a segmented error transformation function is designed. In this case, the terminal cost function is designed to transform an infinite horizon optimal problem into a finite horizon optimal problem. Furthermore, the algorithm via adaptive dynamic programming is developed to optimize the performance index function. The convergence analysis of the iterative algorithm is provided. Since it is almost impossible to directly solve the Hamilton-Jacobi-Bellman (HJB) equation, the reinforcement learning method with neural networks is introduced. Finally, simulation results demonstrate the effectiveness of the proposed optimal control method.

This paper aims to establish a sampled-data framework to solve the consensus problem for multiple heterogeneous Euler-Lagrange systems (MHELSs). The systems under consideration have heterogeneous dynamics and limited communication range. Different from the existing works, the common requirement of not allowing edge disconnection has been relaxed. Firstly, a sampled-data virtual system is constructed to provide reference trajectory for the actual system. The virtual systems only exchange data at sampling instants, so that connectivity requirement only needs to be satisfied at these moments. Next, a prescribed performance controller is proposed to track the reference trajectory and ensure the systems satisfy the relaxed connectivity requirement. Furthermore, an event-triggered mechanism is developed to reduce the update frequency of the controller. To illustrate the effectiveness of the proposed framework, two numerical examples are provided. Note to Practitioners—This paper investigates the connectivity-preserving consensus problem for multiple heterogeneous Euler-Lagrange systems. The Euler-Lagrange system can effectively describe various practical systems, such as autonomous vehicles, robotic manipulators, and walking robots. The integration of virtual and physical systems enables the proposed algorithm to adapt well to heterogeneous multiagent systems. The sampling-data interaction mode of the virtual system ensures a reduction of communication pressure among agents in practice. The design of the direction selector and force limiter effectively maintains reliable communication. The introduction of event-triggering mechanisms reduces the update frequency of physical controllers and lowers the performance requirements of the robot actuators. It is worth mentioning that we relax the connectivity requirement of the topology for the first time. Therefore, it is permissible for the distance between two connected robots to exceed the maximum communication range.

This paper discusses the issue of achieving the prescribed-time formation (PTF) over a directed topology for nonlinear multi-Agent systems (NMASs). A novel PTF protocol framework is proposed through the incorporation of a time-varying function for NMASs. Fuzzy Logic Systems (FLSs) are used to approximate potentially unknown nonlinear functions within the system. It is crucial to note that incorporating the adaptive control technique into the proposed protocol framework eliminates the adverse impact stemming from fuzzy approximation errors. Consequently, the formation errors of each agent converge to zero within the prescribed time. Additionally, through the introduction of a novel adaptive law, the protocol framework is further expanded to the NMASs with disturbances. Both the benefits and efficacy of the presented protocol are shown through numerical examples. Note to Practitioners—This paper delves into the pivotal issue within the realm of NMASs concerning prescribed-time formation control. This paper is motivated by the observation that current practices utilizing fuzzy controllers may not achieve the convergence of system formation errors to zero within the user-defined time frame. To solve this, the introduction of a prescribed-time control methodology is advocated, poised to expedite the formation convergence. Furthermore, the incorporation of an adaptive fuzzy controller is proposed to address challenges stemming from inaccurate system modeling, thereby ensuring the stringent control accuracy. The proposed framework harbors considerable potential for application across diverse industrial contexts, encompassing the realms of mobile robotics, unmanned aerial vehicles, and vehicular traffic management systems. Subsequent research endeavors can delve deeper into refining this approach and investigating methodologies for attaining prescribed time control within switched multi-agent systems.

This article investigates the consensus problem of multiple heterogeneous uncertain Euler–Lagrange systems with limited communication range and input saturation. Due to the heterogeneity of the system, it is difficult to directly design a protocol to achieve consensus. To deal with it, a virtual system framework is proposed such that the consensus problem can be decoupled into two simpler subproblems: consensus among virtual systems and tracking of virtual states by actual agents. Since two agents will lose connection when their distance is greater than limited communication range, large control inputs are required to maintain topological connectivity. However, in practical applications, the existence of input saturation constraints may cause insufficient torque generation and potential connectivity loss. To address this issue, virtual system interaction protection rules are further proposed. The requirements on the connectivity maintenance can be relaxed by allowing temporary disconnections between agents. Finally, a numerical example is provided to verify the effectiveness of the proposed protocol.

A collision-free formation control problem for multiple unmanned aerial vehicles (UAVs) with directed switching topologies and disturbances is investigated. A novel distributed control algorithm that uses UAVs local directed switching information is proposed for achieving the required flight formation and ensuring a safe distance between UAVs; the algorithm involves the incorporation of the APF method in the virtual leader formation scheme. Two command signals generated by the virtual position controller are transmitted to the attitude subsystem. For each UAV, an adaptive composite controller is designed by combining a fuzzy system and fast terminal sliding mode control technique to guarantee that tracking errors converge to a stable area around zero. Finally, the feasibility of the proposed composite control algorithm is demonstrated through a simulation.

This article considers the connectivity-preserving consensus for a class of multiagent systems under the event-triggered mechanism (ETM). By employing the topology hierarchical decomposition method, unnecessary communication interactions can be reduced. Each agent receives state information from one specific agent and sends messages to some other agents. A hybrid ETM is proposed to reduce communication costs and save computational resources for agents. Additionally, distributed state observers are designed to estimate the information of other agents under the ETM. Moreover, a novel connectivity-preserving error function is designed to maintain the connection between two neighboring agents. With the help of this function, a fully distributed connectivity-preserving consensus protocol for the considered multiagent system under directed graphs is proposed. The update of the protocol relies on the designed observer under the ETM. Finally, one example is presented to verify the efficiency of the theoretic designs.

The leader-following formation control is investigated for heterogeneous multiple unmanned surface vehicles with unknown upper bound disturbances and uncertain parameters in this article. Each vehicle has a limited communication range, restricting the information exchange between neighboring vehicles to a specified radius. Due to the limitations of sensors and communication components, the communication frequency between vehicles is taken into account. First, a novel hybrid event-triggered virtual trajectory generation protocol is proposed. In such a protocol, each vessel generates its reference states in real-time without requiring real-time information from its neighbors. Then, by designing error-constrained tracking controller and connectivity-preserving potential function, the initial connectivity of the topology is maintained. Furthermore, fuzzy logic approximation and adaptive control techniques are combined in order to tackle the issues of disturbances and uncertain parameters. Through the Lyapunov method, it is proven that formation errors converge to zero as time approaches infinity. Finally, the effectiveness of the proposed protocol is verified through a simulation involving a cluster of seven vehicles.

In this article, a hybrid event-triggered control protocol is proposed to solve the consensus problem for a class of multiple uncertain Euler–Lagrange systems with limited communication range. The limited communication range will cause the system topology to be time varying. A novel connectivity-preserving mechanism based on the potential function is designed to guarantee the connectivity of initial edges. Then, we introduce an event triggering mechanism to save communication resources. It is noted that connectivity-preserving control often requires continuous communication as the system states needs to be monitored in real time to ensure that the connection will not be destroyed. Thus, it is difficult to combine event-triggered control with connectivity-preserving control. In this article, we design a novel event-triggered hybrid condition without the real-time neighbors’ information and we exclude Zeno behavior. Finally, a numerical example is given to verify the effectiveness of the protocol.