This paper presents control and coordination algorithms for groups of vehicles. The focus is on autonomous vehicle networks performing distributed sensing tasks where each vehicle plays the role of a mobile tunable sensor. The paper proposes gradient descent algorithms for a class of utility functions which encode optimal coverage and sensing policies. The resulting closed-loop behavior is adaptive, distributed, asynchronous, and verifiably correct.

Coverage control for mobile sensing networks

For decreasing communication load and overcoming network constrains, such as the limited bandwidth and data loss in multi-agent networks, this paper integrates the two control strategies to investigate the bounded consensus problem of multi-agent systems (MASs) with external disturbance on the basis of an undirected graph, namely, the quantized control and the event-triggered control. In the existence of the external disturbance, two types of the high-gain control laws with the uniform quantized relative state measurements for the bounded consensus problem of MASs are first discussed, respectively. Then, in order to save the limited network resources in a multi-agent network, the event-triggered quantized communication protocols are designed based on the first case to obtain the bounded consensus in multi-agent systems. Moreover, it is shown that “Zeno behavior” phenomenon can be excluded under the two event-triggered quantized control mechanisms, and the boundness of the relative state error can be adjusted by selecting the different parameters. Finally, two examples are shown to validate the feasibility and efficiency of our theoretical analysis.

Event-Triggered Control for Consensus Problem in Multi-Agent Systems With Quantized Relative State Measurements and External Disturbance

Exponential stability for formation control systems with generalized controllers: A unified approach

This article presents a secure communication scheme based on the quantized synchronization of master–slave neural networks under an event-triggered strategy. First, a dynamic event-triggered strategy is proposed based on a quantized output feedback, for which a quantized output feedback controller is formed. Second, theoretical criteria are derived to ensure the bounded synchronization of master–slave neural networks. With these criteria, an explicit upper bound is given for the synchronization error. Sufficient conditions are also provided on the existence of quantized output feedback controllers. A Chua’s circuit is chosen to illustrate the effectiveness of our theoretical results. Third, a secure communication scheme is presented based on the synchronization of master–slave neural networks by combining the basic principle of cryptology. Then, a secure image communication is studied to verify the feasibility and security performance of the proposed secure communication scheme. The impact of the quantization level and the event-triggered control (ETC) on image decryption is investigated through experiments.

Secure Communication Based on Quantized Synchronization of Chaotic Neural Networks Under an Event-Triggered Strategy

In a networked multiaxis motion control task, faults in any motor will cause the performance degradation of cooperative operation, which may considerably affect the whole network and the quality of products The main objective of this article is to propose an improved observer-based fault-tolerant tracking control approach for industrial multiagent systems First, a group of new distributed intermediate estimators is presented, where the design structure is modified to enhance the feasibility of the estimation scheme It is shown that both of the nominal distributed intermediate estimator and the traditional extended state observer are special cases of the proposed estimator Second, the estimation performance can be improved significantly via an online reinforcement learning estimation strategy, whose core is an adaptive switching mechanism integrated with a function block of source fault mode localization Benefiting from satisfactory estimation results, good fault-tolerant tracking control performance can be guaranteed despite of multiple faults and disturbances The application to a networked multiaxis motion control system demonstrates the effectiveness and superiority of the proposed method

A New Observer-Based Cooperative Fault-Tolerant Tracking Control Method With Application to Networked Multiaxis Motion Control System

This paper proposes three different distributed event-triggered control algorithms to achieve leader–follower consensus for a network of Euler–Lagrange agents. We first propose two model-independent algorithms for a subclass of Euler–Lagrange agents without the vector of gravitational potential forces. By model-independent, we mean that each agent can execute its algorithm with no knowledge of the agent self-dynamics. A variable-gain algorithm is employed when the sensing graph is undirected; algorithm parameters are selected in a fully distributed manner with much greater flexibility compared to all previous work studying event-triggered consensus problems. When the sensing graph is directed, a constant-gain algorithm is employed. The control gains must be centrally designed to exceed several lower bounding inequalities, which require limited knowledge of bounds on the matrices describing the agent dynamics, bounds on network topology information, and bounds on the initial conditions. When the Euler–Lagrange agents have dynamics that include the vector of gravitational potential forces, an adaptive algorithm is proposed. This requires more information about the agent dynamics but allows for the estimation of uncertain parameters associated with the agent self-dynamics. For each algorithm, a trigger function is proposed to govern the event update times. The controller is only updated at each event, which ensures that the control input is piecewise constant and thus saves energy resources. We analyze each controller and trigger function to exclude Zeno behavior.

Event-Triggered Algorithms for Leader–Follower Consensus of Networked Euler–Lagrange Agents

This paper proposes three different distributed event-triggered control algorithms to achieve leader-follower consensus for a network of Euler-Lagrange agents. We firstly propose two model-independent algorithms for a subclass of Euler-Lagrange agents without the vector of gravitational potential forces. By model-independent, we mean that each agent can execute its algorithm with no knowledge of the agent self-dynamics. A variable-gain algorithm is employed when the sensing graph is undirected; algorithm parameters are selected in a fully distributed manner with much greater flexibility compared to all previous work concerning event-triggered consensus problems. When the sensing graph is directed, a constant-gain algorithm is employed. The control gains must be centrally designed to exceed several lower bounding inequalities which require limited knowledge of bounds on the matrices describing the agent dynamics, bounds on network topology information and bounds on the initial conditions. When the Euler-Lagrange agents have dynamics which include the vector of gravitational potential forces, an adaptive algorithm is proposed which requires more information about the agent dynamics but can estimate uncertain agent parameters. 
For each algorithm, a trigger function is proposed to govern the event update times. At each event, the controller is updated, which ensures that the control input is piecewise constant and saves energy resources. We analyse each controllers and trigger function and exclude Zeno behaviour. Extensive simulations show 1) the advantages of our proposed trigger function as compared to those in existing literature, and 2) the effectiveness of our proposed controllers.

Event-Triggered Algorithms for Leader-Follower Consensus of Networked Euler-Lagrange Agents

This paper revisits the circular formation control problem proposed in [G. S. Seyboth, J. Wu, J. Qin, C. Yu, and F. Allgower, “Collective circular motion of unicycle type vehicles with nonidentical constant velocities,” IEEE Transactions on Control of Network Systems , vol. 1, no. 2, pp. 167–176, Jun. 2014.] for multiple nonholonomic mobile robots with nonidentical constant forward speeds. Specifically, we study two types of circular formations: First, a circular motion with synchronized/balanced phase configuration; and second, a concentric circular formation with both circular orbits control and phase synchronization/balancing. Existing works on the above problems utilize a fixed-gain control input, which increases the workload of the engineers for selecting favorable algorithm parameters. To reduce this workload, we study the above problems from a new perspective by utilizing optimization methods, based on which two variable-gain control algorithms are proposed such that much greater flexibility on the selection of algorithm parameters is acquired. The global convergence properties of the proposed algorithms are analyzed under some mild assumptions. Both simulations and field experiments are presented to validate the effectiveness of the proposed formation algorithms.

Circular Formation Algorithms for Multiple Nonholonomic Mobile Robots: An Optimization-Based Approach

This paper discusses generalized controllers for rigid formation shape stabilization. We provide unified analysis to show convergence using different controllers reported in the literature, and further prove an exponential stability of the formation system when using the general form of shape controllers. We also show that different agents can use different controllers for controlling different distances to achieve a desired rigid formation, which enables the implementation of heterogeneous agents in practice for formation shape control. We further propose an event-triggered rigid formation control scheme based on the generalized controllers. The triggering condition, event function and convergence analysis are discussed.

/pdf/generalized-controllers-for-rigid-formation-stabilization-22lvy6213z.pdf

Generalized controllers for rigid formation stabilization with application to event-based controller design

An adaptive, distributed, event-triggered controller is proposed in this paper to study the problem of leader-follower consensus for a directed network of Euler-Lagrange agents. We show that if each agent uses the proposed controller, the leader-follower consensus objective is globally asymptotically achieved if the directed network contains a directed spanning tree with the leader as the root node. We provide a trigger function to govern the event time; at each event time the controller is updated. In doing so, we also obtain an explicit lower bound on the time interval between events and thus we conclude that the proposed controller does not exhibit Zeno behavior. Simulations are provided which show the effectiveness of the proposed controller. Also shown in the simulations is the piecewise constant nature of the control law; this significantly reduces the number of updates required by each actuator, thereby saving energy resources.

/pdf/event-based-leader-follower-consensus-for-multiple-euler-wbaxlin5kl.pdf

Qingchen Liu

Papers

Event-Triggered Algorithms for Leader–Follower Consensus of Networked Euler–Lagrange Agents

Event-Triggered Algorithms for Leader-Follower Consensus of Networked Euler-Lagrange Agents

Circular Formation Algorithms for Multiple Nonholonomic Mobile Robots: An Optimization-Based Approach

Generalized controllers for rigid formation stabilization with application to event-based controller design

Event-based leader-follower consensus for multiple Euler-Lagrange systems with parametric uncertainties