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

Most of the signal processing that we will study in this course involves local operations on a signal, namely transforming the signal by applying linear combinations of values in the neighborhood of each sample point. You are familiar with such operations from Calculus, namely, taking derivatives and you are also familiar with this from optics namely blurring a signal. We will be looking at sampled signals only. Let's start with a few basic examples. Local difference Suppose we have a 1D image and we take the local difference of intensities, DI(x) = 1 2 (I(x + 1) − I(x − 1)) which give a discrete approximation to a partial derivative. (We compute this for each x in the image.) What is the effect of such a transformation? One key idea is that such a derivative would be useful for marking positions where the intensity changes. Such a change is called an edge. It is important to detect edges in images because they often mark locations at which object properties change. These can include changes in illumination along a surface due to a shadow boundary, or a material (pigment) change, or a change in depth as when one object ends and another begins. The computational problem of finding intensity edges in images is called edge detection. We could look for positions at which DI(x) has a large negative or positive value. Large positive values indicate an edge that goes from low to high intensity, and large negative values indicate an edge that goes from high to low intensity. Example Suppose the image consists of a single (slightly sloped) edge:

http://ieeexplore.ieee.org/iel5/5/31307/01456462.pdf

Linear systems

This paper studies a number of quantized feedback design problems for linear systems. We consider the case where quantizers are static (memoryless). The common aim of these design problems is to stabilize the given system or to achieve certain performance with the coarsest quantization density. Our main discovery is that the classical sector bound approach is nonconservative for studying these design problems. Consequently, we are able to convert many quantized feedback design problems to well-known robust control problems with sector bound uncertainties. In particular, we derive the coarsest quantization densities for stabilization for multiple-input-multiple-output systems in both state feedback and output feedback cases; and we also derive conditions for quantized feedback control for quadratic cost and H/sub /spl infin// performances.

The sector bound approach to quantized feedback control | NOVA. The University of Newcastle's Digital Repository

A survey of distributed optimization

This paper presents an adaptive control method for a class of uncertain strict-feedback switched nonlinear systems. First, we consider the constraint characteristics in the switched nonlinear systems to ensure that all states in switched systems do not violate the constraint ranges. Second, we design the controller based on the backstepping technique, while integral Barrier Lyapunov functions (iBLFs) are adopted to solve the full state constraint problems in each step in order to realize the direct constraints on state variables. Furthermore, we introduce the Lyapunov stability theory to demonstrate that the adaptive controller achieves the desired control goals. Finally, we perform a numerical simulation, which further verifies the significance and feasibility of the presented control scheme.

Integral Barrier Lyapunov function-based adaptive control for switched nonlinear systems

This note considers the distributed optimization problem on directed graphs with nonconvex local objective functions and the unknown network connectivity. A new adaptive algorithm is proposed to minimize a differentiable global objective function. By introducing dynamic coupling gains and updating the coupling gains using relative information of system states, the nonconvexity of local objective functions, unknown network connectivity, and the uncertain dynamics caused by locally Lipschitz gradients are tackled concurrently. Consequently, the global asymptotic convergence is established when the global objective function is strongly convex and the gradients of local objective functions are only locally Lipschitz. When the communication graph is strongly connected and weight-balanced, the algorithm is independent of any global information. Then, the algorithm is naturally extended to unbalanced directed graphs by using the left eigenvector of the Laplacian matrix associated with the zero eigenvalue. Several numerical simulations are presented to verify the results.

/pdf/distributed-adaptive-convex-optimization-on-directed-graphs-ym9jzyo5pt.pdf

Distributed Adaptive Convex Optimization on Directed Graphs via Continuous-Time Algorithms

This paper studies the problem of bearing-only formation control of multiagent systems, where the control of each agent merely relies on the relative bearings to its neighbors. Although this problem has received increasing research attention recently, it is still unsolved to a large extent due to its highly nonlinear dynamics. In particular, the existing control approaches are only able to solve the simplest scenario where the target formation is stationary and each agent is modeled as a single integrator. The main contribution of this paper is to propose new bearing-only formation control laws to 1) track moving target formations and 2) handle a variety of agent models including single-integrator, double-integrator, and unicycle models. These control laws are an important step towards the application of bearing-only formation control in practical tasks. Both numerical simulation and real experimental results are presented to verify the effectiveness of the theoretical results.

/pdf/bearing-only-formation-tracking-control-of-multiagent-545t7sxo8b.pdf

Bearing-Only Formation Tracking Control of Multiagent Systems

This note considers the distributed optimal coordination (DOC) problem for heterogeneous linear multiagent systems. The local gradients are locally Lipschitz and the local convexity constants are unknown. A control law is proposed to drive the states of all agents to the optimal coordination that minimizes a global objective function. By exploring certain features of the invariant projection of the Laplacian matrix, the global asymptotic convergence is guaranteed utilizing only local interaction. The proposed control law is then extended with event-triggered communication schemes, which removes the requirement for continuous communications. Under the event-triggered control law, it is proved that no Zeno behavior is exhibited and the global asymptotic convergence is preserved. The proposed control laws are fully distributed, in the sense that the control design only uses the information in the connected neighborhood. Furthermore, to achieve the DOC for linear multiagent systems with unmeasurable states, an observer-based event-triggered control law is proposed. A simulation example is given to validate the proposed control laws.

Distributed Optimal Coordination for Heterogeneous Linear Multiagent Systems With Event-Triggered Mechanisms

The purpose of this study is to test whether consumers' personal colour preferences (in an abstract sense rather than for a particular product) affect their intended product purchase decisions if they are given various colour choices. This work employs two experiments with visual components to investigate which colour a participant would choose if asked to select a product to purchase when there is a range of colours available. Two experiments were also designed to elicit a response about which colour each participant prefers (in an abstract sense). The study finds that personal colour preferences affect intended product-colour purchase decisions but that the extent of this varies from one product category to the next. Further analysis reveals that personal colour preferences are secondary to factors such as colour functionality and colour performance. This work presents new experimental data about the role of colour in product and product packaging on intended consumer purchase decisions. A conceptual framework, supported by the experimental findings, are understanding the relationship between individual colour preferences and product-choice colours, and more functional aspects of colour itself (such as the effect of colour on product's performance or functionality).

/pdf/the-role-of-individual-colour-preferences-in-consumer-1uvpu8ppmn.pdf

The role of individual colour preferences in consumer purchase decisions

In the cooperative simultaneous arrival problem, a group of interceptors are guided to simultaneously engage a stationary target. However, some interceptors may not follow the prescribed guidance law during the engagement, which can lead to interception failures. This brief investigates a new robust cooperative simultaneous arrival problem in the presence of misbehaving interceptors. A robust cooperative guidance law (RCGL) integrated with a local filtering algorithm is designed. Without the knowledge of faulty interceptors (no fault diagnosis procedure is needed), the RCGL achieves a simultaneous arrival between normal interceptors if the misbehavior of faulty interceptors can be characterized by a threat model. By characterizing the contracting behavior of the maximum gap between impact time estimates of normal interceptors, sufficient conditions are established to guarantee the convergence of RCGL. Furthermore, regardless of the network connections, the impact times of normal interceptors are upper bounded by the maximum initial time-to-go estimate of normal interceptors. Numerical comparison studies demonstrate the guidance performance of RCGL.

/pdf/robust-cooperative-guidance-law-for-simultaneous-arrival-2veyr3m90a.pdf

Zhenhong Li

Papers

Distributed Adaptive Convex Optimization on Directed Graphs via Continuous-Time Algorithms

Bearing-Only Formation Tracking Control of Multiagent Systems

Distributed Optimal Coordination for Heterogeneous Linear Multiagent Systems With Event-Triggered Mechanisms

The role of individual colour preferences in consumer purchase decisions

Robust Cooperative Guidance Law for Simultaneous Arrival