In this paper, we study the consensus problem for a class of linear multi-agent systems ( MASs ) with consideration input saturation under self-triggered mechanism. context discrete-time systems, strategy is developed to determine time interval between adjacent triggers. The triggering condition designed by using current sampled error. Furthermore, control protocol means state feedback approach. It shown that considered can reach presented algorithm. Some sufficient conditions are proposed...

To develop a safe and efficient navigation system of robotic vehicles in dynamic scenes, new collision-avoidance method using deep reinforcement learning (DRL) is presented. First, novel DRL based on multithreaded asynchronous proximal policy optimization (MAPPO) developed. It can convert expensive online calculation into an offline training process, improving the sample efficiency during learning. Then, multisensor fusion measurement (MSFM) presented by combination global reference path...

In this article, we investigate a robust distributed model predictive control (DMPC) scheme for tracking the consensus of linear multiagent systems (MASs) subject to additive disturbances and time-varying communication delays. A terminal constraint set is constructed by Lyapunov-Razumikhin functional, corresponding local controller designed each agent. Furthermore, sufficient conditions ensure that provided in form matrix inequalities (LMIs). The recursive feasibility proposed algorithm...

The rapid development of cyber-physical systems technique has promoted the autonomous systems. To perform distributed task autonomously, this study delves into problem resource allocation over second-order multiple physical It aims to minimize global cost function while allocating plenty resources finite agents. Since exogenous disturbances in control channel are unavoidable, and nonlinear dynamical system can more accurately describe behavior system, i.e., Euler–Lagrange term is considered,...

This paper investigates the tracking control problem for unmanned underwater vehicles (UUVs) systems with sensor faults, input saturation, and external disturbance caused by waves ocean currents. An active fault-tolerant scheme is proposed. First, developed method only requires inertia matrix of UUV, without other dynamic information, can handle both additive multiplicative faults. Subsequently, an adaptive controller designed to achieve asymptotic UUV employing robust integral sign error...

A self‐triggered model predictive control (MPC) scheme for continuous‐time perturbed nonlinear systems subject to bounded disturbances is investigated in this study. strategy designed obtain the inter‐execution time before next trigger using current sampled state. An optimisation problem addressed optimal trajectory at each triggered instant. The so‐called dual‐mode approach used stabilise closed‐loop system. Furthermore, sufficient conditions are derived ensure feasibility and stability,...

Distributed primal-dual methods have been widely used for solving large-scale constrained optimization problems. The majority of existing results focus on the problems with decoupled constraints. Some recent works studied subject to separable globally coupled This paper considers distributed constraints over networks without requiring separability is made possible by local estimates constraint violations. For such a problem, we propose algorithm in augmented Lagrangian framework, combining...

This article studies a distributed model-predictive control (DMPC) strategy for class of discrete-time linear systems subject to globally coupled constraints. To reduce the computational burden, constraint tightening technique is adopted enabling early termination optimization algorithm. Using Lagrangian method, we convert constrained problem proposed DMPC an unconstrained saddle-point seeking problem. Due presence global dual variable in function, propose primal-dual algorithm based on...

Distributed aggregative games have been intensely researched due to their wide application in various engineering scenarios. This paper aims address the distributed game over multi-agent system with heterogeneous high-order integrator dynamics and undirected, connected networks. In this game, local objective function incorporates its decision variable an term that combines all agents' variables. The is estimated using consensus method. Therefore, Nash equilibrium-seeking strategy created...

With the rapid development of Transformers in field computer vision, models based on have become highly competitive architectures area. Although variants Transformer achieved increasing accuracy image classification tasks, size training set and number parameters required by increased dramatically. When dealing with small datasets, such face problems as overfitting undergeneralization, leading to poor test set. We propose a new lightweight vision transformer (LVT) address these issues....

An adaptive super-twisting multivariable fast terminal sliding mode control scheme based on time delay estimation (TDE) and asymmetric error constraints are proposed to guarantee high-precision trajectory tracking of cable-driven manipulators under complicated unknown uncertainties. The system is constrained by joint position errors, which time-varying. First, the range joints designed ensure that deviation from desired profile not too large while ensuring safety performance manipulator,...

This paper analyzes the contraction of primal-dual gradient optimization via theory in context discrete-time updating dynamics. The based on Riemannian manifolds is first established for convergence analysis a convex algorithm. equality and inequality constrained cases are studied, respectively. Under some reasonable assumptions, we construct metric to characterize region. It shown that if step-sizes dynamics properly designed, rates both can be obtained according region which guaranteed....

Abstract: In this paper, we study the nonconvex optimization problems with consideration of globally coupled constraints. The constrained problem is converted into an augmented Lagrangian function, and a distributed primal-dual algorithm exploited in context finite-time consensus for solving such problem. Particularly, do not require constraints to be separable. Instead, introduce some local variables estimating constraint violations. Under mild assumptions research optimization, prove...

The distributed constrained optimization problem over an undirected communication topology is investigated in this study. It focuses on addressing a global coupled equality constraint that applies to all agents. To tackle problem, approach with arbitrary initialization developed by virtue of the aperiodic sampling control idea and consensus-based multi-agent system(MAS) technology. This address problems within pre-specified time. In addition, predefined time freely defined users irrelevant...

This paper develops a distributed model predictive control (DMPC) strategy for class of discrete-time linear systems with consideration globally coupled constraints. The DMPC under study is based on the dual problem concerning all subsystems, which solved by means primal-dual gradient optimization in manner using Laplacian consensus. To reduce computational burden, constraint tightening method utilized to provide capability premature termination guaranteeing convergence optimization....