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Automated guided vehicles play a crucial role in transportation and industrial environments. This paper presents a proposed Bio Particle Swarm Optimization (BPSO) algorithm for global path planning. The BPSO algorithm modifies the equation to update the particles' velocity using the randomly generated angles, which enhances the algorithm's searchability and avoids premature convergence. It is compared with Particle Swarm Optimization (PSO), Genetic Algorithm (GA), and Transit Search (TS) algorithms by benchmark functions. It has great performance in unimodal optimization problems, and it gains the best fitness value with fewer iterations and average runtime than other algorithms. The Q-learning method is implemented for local path planning to avoid moving obstacles and combines with the proposed BPSO for the safe operations of automated guided vehicles. The presented BPSO-RL algorithm combines the advantages of the swarm intelligence algorithm and the Q-learning method, which can generate the globally optimal path with fast computational speed and support in dealing with dynamic scenarios. It is validated through computational experiments with moving obstacles and compared with the PSO algorithm for AGV path planning. [ABSTRACT FROM AUTHOR]

This paper considers a class of distributed aggregative games for first-order and second-order integrator-type multi-cluster systems, respectively. Two Nash equilibrium seeking algorithms are designed based on a distributed aggregation observer which is used to estimate the aggregations of the clusters. The convergence is proved by the input-to-state stable method. Moreover, the algorithms are applied to a class of location control problems, that is, distributed nonlinear placement problems for multi-cluster systems. Finally, some simulations are presented to illustrate the effectiveness of the designed algorithms. [ABSTRACT FROM AUTHOR]

This paper considers a class of distributed online aggregative optimization problems over an undirected and connected network. It takes into account an unknown dynamic environment and some aggregation functions, which is different from the problem formulation of the existing approach, making the aggregative optimization problem more challenging. A distributed online optimization algorithm is designed for the considered problem via the mirror descent algorithm and the distributed average tracking method. In particular, the dynamic environment and the gradient are estimated by the averaged tracking methods, and then an online optimization algorithm is designed via a dynamic mirror descent method. It is shown that the dynamic regret is bounded in the order of O (T) . Finally, the effectiveness of the designed algorithm is verified by some simulations of cooperative control of a multi-robot system. [ABSTRACT FROM AUTHOR]

In this paper, the distributed online optimisation problem is considered in an unknown dynamic environment. Compared with the existing results, an unknown dynamic environment causes the problem to be more challenging. An online optimisation algorithm is designed based on distributed mirror descent and distributed average tracking technology. The analysis of dynamic regret is presented and a bounded regret is obtained. Some simulations are given to verify the validity of the designed algorithm. [ABSTRACT FROM AUTHOR]

In this article, the distributed nonlinear placement problem for a class of multicluster Euler–Lagrange systems is considered. The problem is first converted into a time-varying noncooperative game. A distributed Nash equilibrium seeking algorithm composed of an auxiliary double-integrator system and a coordinated-tracking observer is designed to solve the problem. The convergence results are established by an iterative approach and the small gain theorem. The effectiveness of the algorithm is demonstrated via simulations. [ABSTRACT FROM AUTHOR]

In this article, the consensus, collision avoidance, and distributed convex optimization problems of a class of multi‐agent systems with a time‐varying objective function are studied. Moreover, the proposed method in this article can reduce the chattering problem of the controller input caused by the sign function. First, the sign function is used to design the controller to improve the convergence rate of the system, on this basis, the optimization item is designed for the more complex time‐varying objective function to ensure that the value of the objective function is the smallest when the system achieves the speed consensus. Second, considering the chattering problem caused by the sign function, the designed controller is improved to reduce the chattering phenomenon. Third, two novel Lyapunov functions are constructed to verify the stability of the system and the distributed optimization objective. Due to the controller is designed for the time‐varying objective function, moreover, the tasks of the formation and collision avoidance are needed to take into account, therefore, the designed Lyapunov functions in this article are more difficult. Finally, the formation function is designed to ensure that the multi‐agent system achieves the desired formation configuration. The simulation results show the correctness of the theoretical design of this article and the superiority in extending the running time of the system. [ABSTRACT FROM AUTHOR]

In this article, a class of distributed quadratic games is considered over an undirected graph. The issue on the communication topology restriction is introduced and the players’ dynamics are with nonlinear dynamics and unknown time-varying perturbation. A distributed Nash equilibrium seeking algorithm is proposed based on a high-gain observer method, and the convergence is analyzed by the Lyapunov stability theory. It is shown that each player estimates the rival players’ states, and the errors between the players’ states and the Nash equilibrium are ultimately bounded by a small bound. Moreover, the presented algorithm is free of chattering phenomena because it is designed using the hyperbolic tangent function instead of the signum function to dominant the perturbation. The effectiveness of the proposed algorithm is validated via a simulation of the oligopoly game in which five firms produce the same products in a duopoly market structure. [ABSTRACT FROM AUTHOR]

The distributed time‐varying constrained convex optimization problem over a connected undirected network topology is studied in this article. The proposed distributed optimization algorithm is composed of a projection map term, a consensus term, and a gradient term, and is feasible for any initial condition. We first show that the states of the optimization algorithm uniformly converge to a neighborhood of the constraint set while an approximate global consensus is achieved. Then the states are proven to uniformly converge to a neighborhood of the time‐varying optimal trajectory. The theoretical results are validated by some simulations. [ABSTRACT FROM AUTHOR]

The distributed economic dispatch problem for power generation in electricity grids is studies. A simple centralised algorithm is designed to obtain the solution of the dispatch problem without the external disturbances. Inspired by the centralised algorithm, a distributed algorithm is presented using the distributed average tracking algorithm. As far as we know, the proposed algorithm is the first one that is capable of time‐varying loads and external disturbances while the tracking errors are asymptotic convergent. Simulations on the IEEE 14‐BUS system are provided to validate the theoretical results. [ABSTRACT FROM AUTHOR]

In this study, the distributed optimisation problem for linear multi‐agent systems with disturbance rejection is considered. The topology graph is assumed to be uniformly jointly strongly connected and the disturbance is not limited to satisfy the matching condition. Each agent is assigned with a local quadratic cost function and the objective is to minimise the sum of local cost functions based on information exchange. The authors propose a distributed observer for each agent such that other agents' cost functions are obtained. Then, the state feedback and output feedback optimal algorithms are designed based on the output of the distributed observer. The theoretical results are validated by simulations. [ABSTRACT FROM AUTHOR]

Abstract: This paper considers semi‐global robust output regulation problem for a class of singular nonlinear systems whose algebraic equations are not precisely known. Since the algebraic equations are not known, the output regulation problem of singular nonlinear systems cannot be solved by directly reducing the singular nonlinear system into a normal nonlinear system. Based on internal model principle, we convert the robust output regulation problem of singular nonlinear systems into a robust stabilization problem of an augmented singular nonlinear system. The augmented singular nonlinear system is also with unknown algebraic equations. However, without transforming the singular nonlinear system into a normal nonlinear system, it is shown that the augmented singular nonlinear system can be semi‐globally stabilized by a high gain output feedback control law under some reasonable assumptions. Moreover, the semi‐global stabilization control law of the augmented singular nonlinear systems also solves the semi‐global robust output regulation problem of the original singular nonlinear system. [ABSTRACT FROM AUTHOR]

This study considers the cooperative global output regulation problem for a class of non‐linear multi‐agent systems. In particular, the authors consider the case that the exosystem is of a non‐linear form. With a distributed non‐linear observer of the exosystem and the solvability assumption of the regulator equations, the authors convert the problem into a global cooperative stabilisation problem. Sufficient conditions are derived for the global cooperative stabilisation problem under fixed directed network topologies and switching undirected network topologies, respectively. Finally, the validity of the proposed approach is illustrated by simulation results. [ABSTRACT FROM AUTHOR]

Most of existing results on robust output regulation problem of singular nonlinear systems are limited to local solutions. In this paper, the semi-global robust output regulation problem for a class of singular nonlinear systems is investigated by using a nonlinear internal model. Attaching a nonlinear internal model to the singular nonlinear system yields an augmented singular nonlinear system whose semi-global robust stabilisation solution leads to the solution of the semi-global robust output regulation problem of the original singular nonlinear system. The solvability conditions of the semi-global output regulation problem are established by addressing the solvability of the robust stabilisation problem of augmented singular nonlinear system. Finally, a numerical simulation example is used to illustrate the design of the semi-global regulator for the singular nonlinear systems. [ABSTRACT FROM AUTHOR]

Purpose The purpose of this paper is to investigate microstructure and properties of Sn3.0Ag0.5Cu-XAl2O3 composite solder which were prepared through powder metallurgy route.Design/methodology/approach Sn3.0Ag0.5Cu (SAC305)-XAl2O3 (X = 0.2, 0.4, 0.6, 0.8 Wt. %) composite solders were prepared through the powder metallurgy route. The morphology of composite solder powders which consists of Al2O3 particles and SAC solder powders after ball milling was observed. The retained ratio of Al2O3 nanoparticles in composite solder billets and solder joints were also quantitatively measured. Furthermore, the as-prepared composite solder alloys were studied extensively with regard to their microstructures, thermal property, wettability and mechanical properties.Findings After ball milling, the Al2O3 nanoparticles added were observed embedded into the surface of SAC solder powders. Only about 5-10 per cent of the initial Al2O3 nanoparticles added were detected in the composite solder joints after reflow. In addition, finer ß-Sn grains were achieved with addition of Al2O3 nanoparticles; the Al2O3 nanoparticles were found retained in the composite solder matrix. Besides, negligible changes in melting temperature and the considerably reduced undercooling were obtained in composite solder alloys. Wettability was improved by appropriate addition of Al2O3 nanoparticles. Microhardness and shear strength of composite solders were both improved after Al2O3 nanoparticles addition.Originality/value This paper indicated that powder metallurgy route offered a feasible approach to produce nanoparticle reinforced composite solder. In addition, the quantitative analysis of the actual retained ratio of the Al2O3 nanoparticles in solder joints provided practical implications for the manufacture of composite solders. [ABSTRACT FROM AUTHOR]

The optimization problem of second-order discrete-time multiagent systems with set constraints is studied in this article. In particular, the involved agents cooperatively search an optimal solution of a global objective function summed by multiple local ones within the intersection of multiple constrained sets. We also consider that each pair of local objective function and constrained set is exclusively accessible to the respective agent, and each agent just interacts with its local neighbors. By borrowing from the consensus idea, a projection-based distributed optimization algorithm resorting to an auxiliary dynamics is first proposed without interacting the gradient information of local objective functions. Next, by considering the local objective functions being strongly convex, selection criteria of step size and algorithm parameter are built such that the unique solution to the concerned optimization problem is obtained. Moreover, by fixing a unit step size, it is also shown that the optimization result can be relaxed to the case with just convex local objective functions given a properly chosen algorithm parameter. Finally, practical and numerical examples are taken to verify the proposed optimization results.

In this article, a class of distributed nonlinear placement problems is considered for a multicluster system. The task is to determine the positions of the agents in each cluster subject to the constraints on agent positions and the network topology. In particular, the agents in each cluster are placed to form the desired shape and minimize the sum of squares of the Euclidean lengths of the links amongst the center of each cluster and its corresponding cluster members. The problem is converted into a time-varying noncooperative game and then a distributed Nash equilibrium-seeking algorithm is designed based on a distributed observer method. A new iterative approach is employed to prove the convergence with the aid of the Lyapunov stability theorem. The effectiveness of the distributed algorithm is validated by numerical examples.