Decentralized estimation and control of graph connectivity for mobile sensor networks

The ability of a robot team to reconfigure itself is useful in many applications: for metamorphic robots to change shape, for swarm motion towards a goal, for biological systems to avoid predators, or for mobile buoys to clean up oil spills. In many situations, auxiliary constraints, such as connectivity between team members or limits on the maximum hop-count, must be satisfied during reconfiguration. In this paper, we show that both the estimation and control of the graph connectivity can be accomplished in a decentralized manner. We describe a decentralized estimation procedure that allows each agent to track the algebraic connectivity of a time-varying graph. Based on this estimator, we further propose a decentralized gradient controller for each agent to maintain global connectivity during motion.     

Intra-domain routing convergence with centralized control

The decentralized control scheme for routing in current IP networks has been questioned, and a centralized routing scheme has been proposed as an alternative. In this paper, we compare the convergence of centralized control scheme with decentralized link-state routing protocols. We first review the architectural advantages and challenges of centralized control. Thereafter, we identify and discuss the components of the convergence time in both schemes. We present how to achieve fast routing convergence in networks with centralized control. In particular, we analyze how to distribute forwarding information efficiently. Finally, we perform simulation studies on the convergence time for both real and synthetic network topologies and study the impact of control element location, link weights, and number of failures on the convergence time. The results show that the centralized control scheme can provide faster routing convergence than link-state routing protocols.     

Arbitrarily shaped formations of mobile robots: artificial potential fields and coordinate transformation

In this paper we describe a novel decentralized control strategy to realize formations of mobile robots. We first describe how to design artificial potential fields to obtain a formation with the shape of a regular polygon. We provide a formal proof of the asymptotic stability of the system, based on the definition of a proper Lyapunov function. We also prove that our control strategy is not affected by the problem of local minima. Then, we exploit a bijective coordinate transformation to deform the polygonal formation, thus obtaining a completely arbitrarily shaped formation. Simulations and experimental tests are provided to validate the control strategy.     

Coordinated management of hardware and software self-adaptivity

Self-adaptivity is the capability of a system to adapt itself dynamically to achieve its goals. Self-adaptive systems will be widely used in the future both to efficiently use system resources and to ease the management of complex systems. The frameworks for self-adaptivity developed so far usually concentrate either on self-adaptive software or on self-adaptive hardware, but not both.In this paper, we propose a model of self-adaptive systems and we describe how to manage self-adaptivity at all levels (both hardware and software) by means of a decentralized control algorithm. The key advantage of decentralized control is in the simplicity of the local controllers. Simulation results are provided to show the main characteristics of the model and to discuss it.     

分散自校正控制算法及其全局收敛性分析

本文基于分散控制和自校正控制的思想，提出一种大系统分散自校正控制算法，在研究某个子系统时，把其它子系统的影响等价为可测干扰，对各子系统采用本文提出的多变量自校正控制算法，从而实现大系统的整体控制，仿真结果表明对大系统采用分散自校正控制是行之有效的。算法的全局收敛性和参数估计强相容性也得到了证明。     

最优控制理论在磁轴承控制系统中的应用研究

建立了径向四自由度磁轴承系统状态方程, 介绍了采用最优控制理论中线性二次型方法设计磁轴承集中和分布参数控制器的方法和步骤, 并用MATLAB语言进行了仿真比较. 仿真和实验结果表明: 磁轴承转子在 60000rpm以下运行, 基于最优状态反馈控制理论设计的控制器, 忽略各自由度之间的耦合, 用分散控制策略设计的磁轴承控制系统, 基本满足磁轴承性能要求.     

Policy-constrained bio-inspired processes for autonomic route management

Autonomic networking systems must be designed to achieve an appropriate balance between the operation of decentralized algorithms and processes that seek to maintain optimal or near-optimal behavior in terms of global stability, improved performance and adaptability, robustness and security, with the requirement for top-down control of the system by humans to ensure business goals are met. Taking a communications networking survivability case study, we show how the operation of decentralized algorithms, inspired by the operation of biological systems, can be controlled and constrained through the deployment of management policies authored by network administrators. We present survivability-related routing algorithms (inspired by chemotaxis, reaction-diffusion and quorum sensing biological processes) which work together to effectively reconfigure network resources when transient link failures occur and demonstrate how these algorithms can be re-parameterized via policies to improve performance given prevailing network conditions. Simulation results show how the combined operation of these algorithms, as controlled by policies, allows the network to react well to survive link failure events.     

On the stability and control of nonlinear dynamical systems via vector Lyapunov functions

Vector Lyapunov theory has been developed to weaken the hypothesis of standard Lyapunov theory in order to enlarge the class of Lyapunov functions that can be used for analyzing system stability. In this paper, we extend the theory of vector Lyapunov functions by constructing a generalized comparison system whose vector field can be a function of the comparison system states as well as the nonlinear dynamical system states. Furthermore, we present a generalized convergence result which, in the case of a scalar comparison system, specializes to the classical Krasovskii-LaSalle invariant set theorem. In addition, we introduce the notion of a control vector Lyapunov function as a generalization of control Lyapunov functions, and show that asymptotic stabilizability of a nonlinear dynamical system is equivalent to the existence of a control vector Lyapunov function. Moreover, using control vector Lyapunov functions, we construct a universal decentralized feedback control law for a decentralized nonlinear dynamical system that possesses guaranteed gain and sector margins in each decentralized input channel. Furthermore, we establish connections between the recently developed notion of vector dissipativity and optimality of the proposed decentralized feedback control law. Finally, the proposed control framework is used to construct decentralized controllers for large-scale nonlinear systems with robustness guarantees against full modeling uncertainty.     

多关节机器人的分散预测控制*

本文提出一种对多关节机器人进行分散预测控制的方法,这种方法把分散控制的结构优点与预测控制的性能优点结合起来,以提高控制的实时性和鲁棒性。文中研究了这一分散控制的多层结构,并着重讨论了不同分散信息结构下的关连预测策略,最后以仿真实例说明了这种分散预测控制方法的有效性。     

Decentralized Guidance Control of UAVs with Explicit Optimization of Communication

We design a decentralized guidance control method for autonomous unmanned aerial vehicles (UAVs) tracking multiple targets. We formulate this guidance control problem as a decentralized partially observable Markov decision process (Dec-POMDP). As in the case of partially observable Markov decision process (POMDP), it is intractable to solve a Dec-POMDP exactly. So, we extend a POMDP approximation method called nominal belief-state optimization (NBO) to solve our control problem posed as a Dec-POMDP. We incorporate the cost of communication into the objective function of the Dec-POMDP, i.e., we explicitly optimize the communication among the UAVs at the network level along with the kinematic control commands for the UAVs. We measure the performance of our method with the following metrics: 1) average target-location error, and 2) average communication cost. The goal to maximize the performance with respect to each of the above metrics conflict with each other, and we show through empirical study how to trade off between these performance metrics using a scalar parameter. The NBO method induces coordination among the UAVs even though the system is decentralized. To demonstrate the effectiveness of this coordination, we compare our Dec-POMDP approach with a greedy approach (a noncooperative approach), where the UAVs do not communicate with each other and each UAV optimizes only its local kinematic controls. Furthermore, we compare the performance of our approach of optimizing the communication between the UAVs with a fixed communication scheme—where only the UAV kinematic controls are optimized with an underlying fixed (non-optimized) communication scheme.     

Decentralized Bayesian Search Using Approximate Dynamic Programming Methods

We consider decentralized Bayesian search problems that involve a team of multiple autonomous agents searching for targets on a network of search points operating under the following constraints: 1) interagent communication is limited; 2) the agents do not have the opportunity to agree in advance on how to resolve equivalent but incompatible strategies; and 3) each agent lacks the ability to control or predict with certainty the actions of the other agents. We formulate the multiagent search-path-planning problem as a decentralized optimal control problem and introduce approximate dynamic heuristics that can be implemented in a decentralized fashion. After establishing some analytical properties of the heuristics, we present computational results for a search problem involving two agents on a 5 times 5 grid.     

Designing Stable Finite State Machine Behaviors Using Phase Plane Analysis and Variable Structure Control

This paper discusses how phase plane analysis can be used to describe the overall behavior of single and multiple autonomous robotic vehicles with finite state machine rules. The importance of this result is that we can begin to design provably stable group behaviors from a set of simple control laws and appropriate switching points with decentralized variable structure control. The ability to prove stable group behavior is especially important for applications such as locating military targets or land mines. In this paper, we demonstrate how phase plane analysis has been used to explain the behavior of a 16 cm³ autonomous line-tracking robot with four finite states. After which, the analysis is extended to include the design of a decentralized variable structure controller that guides multiple vehicles to a goal while avoiding each other.     

Robust feedback stabilization of underwater robotic vehicles

The controlled motion of an underwater vehicle is very likely to be affected by arbitrary disturbances with considerable magnitudes. In this paper, we develop a simple approach for optimal robust control design of underwater robotic vehicles having decentralized input-output structure. Our design method is based on an explicit condition on the control input matrix which has been found to be necessary and sufficient for a decentralized control system to be robust against arbitrary, but otherwise, bounded disturbances. That makes it possible to get optimal trade-off relations between the bounds of disturbances, the system output accuracy, and the control force limits. For the robust control design purpose, we apply decentralized sliding-mode control the stability of which can be easily verified using Lyapunov theory. In order to show the effectiveness of the design method, the controlled planar motion of an underwater robotic vehicle is taken as an illustrative example.     

多智能体机器人系统分布式通信决策研究

无偿通信可以将Multi-agent POMDP的计算复杂度简化为单Agent POMDP的，然而实际上通信不是无偿的，常常期望减少通信的数量。为此提出了一个新的方法，利用有向无环图维持以及推理团队的可能联合信度，基于此以分布式的方式制定通信决策，并将集中式单Agent策略应用于分布式Multi-agent POMDP问题。通过实验以及一个详细的实例表明本文方法能够有效地减少通信资源的使用，同时提高分布执行的性能。     

Designing Decentralized Controllers for Distributed-Air-Jet MEMS-Based Micromanipulators by Reinforcement Learning

Distributed-air-jet MEMS-based systems have been proposed to manipulate small parts with high velocities and without any friction problems. The control of such distributed systems is very challenging and usual approaches for contact arrayed system don’t produce satisfactory results. In this paper, we investigate reinforcement learning control approaches in order to position and convey an object. Reinforcement learning is a popular approach to find controllers that are tailored exactly to the system without any prior model. We show how to apply reinforcement learning in a decentralized perspective and in order to address the global-local trade-off. The simulation results demonstrate that the reinforcement learning method is a promising way to design control laws for such distributed systems.     

Decentralized supervisory control of nondeterministic discrete event systems: The existence condition of a robust and nonblocking supervisor

This paper addresses a decentralized supervisory control problem for an uncertain discrete event system (DES) modeled by a set of possible nondeterministic automata with unidentified internal events. For a given language specification, we present the existence condition of a robust and nonblocking decentralized supervisor that achieves this specification for any nondeterministic model in the set. In particular, we show that the given language specification can be achieved based on the properties of its controllability and coobservability with respect to the overall nominal behavior of the uncertain DES. It is further shown that the existence of a nonblocking decentralized supervisor can be examined with a trajectory model of the language specification.     

Optimal Signaling Policies for Decentralized Multicontroller Stabilizability Over Communication Channels

In this note, we study the problem of distributed control over communication channels, where a number of distributed stations collaborate to stabilize a linear system. We quantify the rate requirements and obtain optimal signaling, coding and control schemes for decentralized stabilizability in such multicontroller systems. We show that in the absence of a centralized decoder at the plant, there is in general a rate loss in decentralized systems as compared to a centralized system. This result is in contrast with the absence of rate loss in the stabilization of multisensor systems. Furthermore, there is rate loss even if explicit channels are available between the stations. We obtain the minimum data rates needed in terms of the open-loop system matrix and the connectivity graph of the decentralized system, and obtain the optimal signaling policies. We also present constructions leading to stability. In addition, we show that if there are dedicated channels connecting the controllers, rate requirements become more lenient, and as a result strong connectivity is not required for decentralized stabilizability. We determine the minimum number of such external channels leading to a stable system, in case strong connectivity is absent.     

关联大系统的分散开环回路传递再

基于H∞理论和分散状态观测器,提出了不确定性关联大系统的分散开环回路传递再生 方法.给出了满足开环再生矩阵H∞范数要求的观测器的存在性.在大系统关联项块对角 奇异值分解的基础上,证明了通过解Riccati方程可以求得使开环再生差阵满足要求的分散 观测器增益阵,以实现分散开环传递再生.试验结果表明,分散开环回路传递再生控制性能 与分散状态反馈控制性能基本相同.     

Suboptimality of decentralized stochastic control and estimation

A stochastic version of suboptimal decentralized control is formulated to study the effects of interactions on performance of systems which are composed of locally optimal subsystems. Turning this approach the other way, we also investigate suboptimality of the decentralized control which arises from the globally optimal control of the overall interconnected system due to the loss of feedback control connections among the subsystems. Various characterizations of suboptimality are given in terms of interconnection and feedback gain matrices. By duality, we derive the suboptimality conditions for decentralized estimation. The separate solutions of control and estimation problems are used to provide a suboptimal decentralized design for incomplete state information. Additional conditions are obtained for robustness and reliability of the interconnected systems synthesized by a suboptimal decentralized control.     

Reliable decentralized supervisory control of discrete eventsystems

We consider a discrete event system controlled by a decentralized supervisor consisting of n local supervisors, and formulate a new decentralized supervisory control problem, called a reliable decentralized supervisory control problem. A decentralized supervisor is said to be k-reliable (1相似文献