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A cooperative multi-agent system entitles some independent agents to complete complex tasks through coordination and cooperation. Since the dynamics of physical agents are so complex that the environment of learning is indeed stochastic, the paper introduces the decentralized multi-agent reinforcement learning (MARL) algorithm, named as Decentralized Concurrent Learning with Cooperative Policy Exploration...
In this paper, a multi-agent distributed continuous-time algorithm is proposed to solve a large-scale linear algebraic equation Ax = do. Unlike many existing results assuming each agent knows a few rows of A, the algorithm proposed in this paper assumes each agent knows a few columns of A. To solve the linear algebraic equation, the problem is first converted to an optimization problem with a linear...
In consideration of the uncertain and time-varying driving resistance in vehicle dynamics, a distributed adaptive sliding model control protocol is proposed in vehicle platoon control. Firstly, the vehicle resistance, which is relevant to vehicle mass, weather conditions, deadweight, motorcycle type and etc, is analyzed and the vehicle platoon model is established. Then, a coupled sliding mode surface...
In this paper, a generalized convex network optimization problem with local domains and constraints is formulated and solved by using distributed multi-agent dynamics. Within the framework of the present network optimization, it is assumed that the local system states and constraints are available to an individual agent and each agent may only share information with its neighbors. A distributed PI-based...
This paper proposes a new approach for robust pole assignment in second-order systems with proportional plus derivative state feedback. The desired closed-loop poles set locates in an arbitrarily specified circular region, and it can be easily taken as a part of the design parameters based on geometric principles. The object can be converted into a global dynamical optimization problem based on geometric...
Recently, rapidly-exploring random trees(RRT) is widely used in path planning for its nature of single-query. The optimized algorithm RRT∗ extends RRT algorithm to find the optimal path, but it needs to search every state from the initial state to the global scope asymptotically. This method is not only inefficient, but also contrary to the single-query of RRT. In this paper, a new variant of RRT∗-Gb...
In this paper, A solution is proposed for the multi-robot task assignment in obstacle environment, which combines the A∗ algorithm with the genetic algorithm. Our main work are twofold:(a) Path planning method based on A∗ algorithm to search an optimal path between any robot and any target or any two targets; and (b) task assignment method based on the genetic algorithm for the assignment of robots...
Correct knowledge of noise statistics is essential for an effective estimator in maneuvering target tracking. In practice, however, the noise statistics are usually unknown or not perfectly known. To deal with the estimation problem in linear discrete-time systems with Markov jump parameters, where the measurement noise covariance is unknown, a novel approach is presented in this paper. This approach...
In this paper, we investigate a distributed Nash equilibrium seeking problem for aggregative games with nonlinear aggregation generators. In our game model, the strategic interaction is associated with a sum of heterogeneous nonlinear mapping of local decisions, and the local cost functions are non-quadratic with the decision variables limited in local constraint sets. We propose a novel discrete-time...
This paper proposes a distributed controller to optimize a sum of state-dependent vector objective functions for multi-Autonomous Underwater Vehicle (AUV) systems. In particular, each AUV has a local private objective and can only interact with its neighboring AUVs, which are described by undirected graphs, to measure relative states. Using 6 degree of freedom (DOF) AUV equations of motions, we design...
This paper addresses the formation keeping of a network of Port-Controlled Hamiltonian(PCH) AUV multi-agent systems. The objective is solved by interconnecting agents with virtual couplings based on the internal principle, which can look into the energy consumption. Firstly, the controller for tracking estimated velocity is designed by ultilizing Hamiltonian theory. We assume that the desired velocity...
A model predictive control algorithm of closed-loop supply chain networks dynamic system is studied. Based on the established system prediction model, the calculation formula of state estimation and prediction are given; the multi-stage optimal prediction model expressions are deduced; the objective function and the feedback correction method are given; the constrained optimization algorithm based...
In this paper, the state estimation problem is investigated for a class of nonlinear stochastic systems. In order to deal with the effects of missing measurements, a consensus-based unscented Kalman filtering algorithm is presented on the basis of distributed sensor networks. Moreover, a sufficient condition is derived to ensure that the estimate error is bounded in mean square. Finally, simulation...
Adaptive Dynamic Programming (ADP) with critic-actor architecture is a useful way to achieve online learning control. The algorithm Gaussian-Kernel Adaptive Dynamic Programming (GK-ADP) that has been developed before has a kind of two-phase iteration, which not only approximates value function, but also optimizes hyper-parameters simultaneously. However, just like most iteration algorithms are applied...
The walking control on level ground of a semi-passive biped robot is studied. Firstly, the dynamic equation of the swing phase is derived using the Euler-Lagrange method, and the transition model at heelstrike collision is derived based on conservation of angular momentum and impulse-momentum equations. Then a toe-off impulse is applied to the stance leg just before heelstrike. The initial impulse...
In the Underwater Transportation processing, the fixed set-point control of a dynamic positioning system enables an unmanned underwater vehicle (UUV) automatically to move to a set position by means of a control system, as well as to maintain its precision when deviating from that set position. In response, this paper aims to improve its generalization ability by indirectly pruning the structure of...
This paper investigates the problem of formation control for multi-agent systems with general linear dynamics and input saturation. The time-varying formation tracking this paper deal with is required to be piecewise differentiable. Firstly, a time-varying formation control protocol is presented. Then an algorithm consisting of 3 steps to design the formation control protocol is proposed. As follows,...
This paper discusses the novel anti-disturbance control algorithm for hypersonic flight vehicle (HFV) models by using neural network (NN) identifier. Different from those existed anti-disturbance results, the unknown exogenous disturbances in HFV models are assumed to be described by the designed NNs with adjustable parameters. Furthermore, the disturbance-observer-based-control (DOBC) algorithm with...
In real-world applications, a majority of optimization problems belong to dynamic optimization, which involves optimization over time and whose underlying space is infinite-dimensional. In this paper, a novel dynamic optimization technique based on state transition algorithm (STA) is investigated to solve dynamic optimization problems (DOPs). Firstly, an infinite dynamic optimization problem is converted...
The trajectory optimization with dynamic headway for high-speed trains plays an important role in railway operations with the increasing passenger flow. Safety, punctuality, energy saving and comfort are some of the most crucial objectives that are considered in train tracking process in this paper. Primarily, the multi-objective optimization model of tracking train trajectory planning is built under...
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