On Radar Deception, As Motivation For Control Of Constrained Systems

This thesis studies the control algorithms used by a team of ECAVs (Electronic Combat Air Vehicle) to deceive a network of radars to detect a phantom track. Each ECAV has the electronic capability of intercepting the radar waves, and introducing an appropriate time delay before transmitting it back, and deceiving the radar into seeing a spurious target beyond its actual position. On the other hand, to avoid the errors and increase the reliability, have a complete coverage in various atmosphere conditions, and confronting the effort of the belligerent intruders to delude the sentinel and enter the area usually a network of radars are deployed to guard the region. However, a team of cooperating ECAVs could exploit this arrangement and plans their trajectories in a way all the radars in the network vouch for seeing a single and coherent spurious track of a phantom. Since each station in the network confirms the other, the phantom track is considered valid. This problem serves as a motivating example in trajectory planning for the multi-agent system in highly constrained operation conditions. The given control command to each agent should be a viable one in the agent limited capabilities, and also drives it in a cumulative action to keep the formation. In this thesis, three different approaches to devise a trajectory for each agent is studied, and the difficulties for deploying each one are addressed. In the first one, a command center has all information about the state of the agents, and in every step decides about the control each agent should apply. This method is very effective and robust, but needs a reliable communication. In the second method, each agent decides on its own control, and the members of the group just communicate and agree on the range of control they like to apply on the phantom. Although in this method much less data needs to communicate between the agents, it is very sensitive to the disturbances and miscalculations, and could be easily fell apart or come to a state with no feasible solution to continue. In the third method a differential geometric approach to the problem is studied. This method has a very strong backbone, and minimizes the communication needed to a binary one. However, less data provided to the agents about the system, more sensitive and infirm the system is when it faced with imperfectionalities. In this thesis, an object oriented program is developed in the Matlab software area to simulate all these three control strategies in a scalable fashion. Object oriented programming is a naturally suitable method to simulate a multi-agent system. It gives the flexibility to make the code more iv close to a real scenario with defining each agent as a separated and independent identity. The main objective is to understand the nature of the constrained dynamic problems, and examine various solutions in different situations. Using the flexibility of this code, we could simulate several scenarios, and incorporate various conditions on the system. Also, we could have a close look at each agent to observe its behavior in these situations. In this way we will gain a good insight of the system which could be used in designing of the agents for specific missions

Bayesian Optimization-based Nonlinear Adaptive PID Controller Design for Robust Mobile Manipulation

In this paper, we propose to use a nonlinear adaptive PID controller to regulate the joint variables of a mobile manipulator. The motion of the mobile base forces undue disturbances on the joint controllers of the manipulator. In designing a conventional PID controller, one should make a trade-off between the performance and agility of the closed-loop system and its stability margins. The proposed nonlinear adaptive PID controller provides a mechanism to relax the need for such a compromise by adapting the gains according to the magnitude of the error without expert tuning. Therefore, we can achieve agile performance for the system while seeing damped overshoot in the output and track the reference as close as possible, even in the presence of external disturbances and uncertainties in the modeling of the system. We have employed a Bayesian optimization approach to choose the parameters of a nonlinear adaptive PID controller to achieve the best performance in tracking the reference input and rejecting disturbances. The results demonstrate that a well-designed nonlinear adaptive PID controller can effectively regulate a mobile manipulator's joint variables while carrying an unspecified heavy load and an abrupt base movement occurs

A review of source term estimation methods for atmospheric dispersion events using static or mobile sensors

Understanding atmospheric transport and dispersal events has an important role in a range of scenarios. Of particular importance is aiding in emergency response after an intentional or accidental chemical, biological or radiological (CBR) release. In the event of a CBR release, it is desirable to know the current and future spatial extent of the contaminant as well as its location in order to aid decision makers in emergency response. Many dispersion phenomena may be opaque or clear, thus monitoring them using visual methods will be difficult or impossible. In these scenarios, relevant concentration sensors are required to detect the substance where they can form a static network on the ground or be placed upon mobile platforms. This paper presents a review of techniques used to gain information about atmospheric dispersion events using static or mobile sensors. The review is concluded with a discussion on the current limitations of the state of the art and recommendations for future research.close

Geometric Control of a Constrained System: Cooperative Action with a Coordinated Multiagent System

Abstract In this work we examine a differential geometric approach towards the synthesis of trajectory for each member of a team of autonomous surface vehicles which are cooperating to perform a coordinated act. In this framework the procedure of trajectory planning is done in decentralized fashion as a closed-loop control for each of the agent which is drawing feedback from the state of the consensus point of the team. The coordination/cooperation between the members of the group is minimum and limits to the common objective of the team to drive the consensus point on a predefined trajectory. The problem is formulated as trajectory planning for the agents of the cooperation. The agents are subjected to various holonomic and nonholonomic constraints on their state variables. The holonomic constraints mainly arise from arise from the dynamic of the agents, and the non-holonomic constraints are between the agents participating in the cooperation. With unifying both these seemingly different constraints we concentrate on addressing other difficulties of the problem, such as the hard constraint on the control and speed variables of the system. To embolden the significance of the solution this research proposes we have applied this method for a team consists of several micro Autonomous Surface Vehicles (mASVs) which are to be coordinated to transport a buoyant load. The mASVs have limited dynamic and kinematic capabilities. These limitations are modeled as bounds on the Force and torque inputs and speed and angular velocities of the extended unicycle models which represent each vehicle. The particular formulation of ours provides us with tools to corporate these limitations in the design of the trajectories and come up with a feasible solution to the problem. We exploit the power and flexibility of the mathematical tools that differential geometry provides us to synthesize an optimal solution for this highly constrained problem. We start with examining the holonomic and nonholonomic constraints on the states of the participating vehicles, and continue to design a trajectory for the total system in its kinematic space. At this stage a trajectory is designed for the load, and consequent trajectories are derived for the vehicles. The next step is to introduce dynamics to the model of the agents. This will eliminated the secondary controller which was necessary to implement for each agent to follow the devised kinematic trajectory. Since the dynamics of the agents appears in the formulation, the trajectories are designed such that the actions of the agents are being optimized.Ph.D., Mechanical Engineering and Mechanics -- Drexel University, 201

Correction: Hajieghrary, H.; Mox, D.; Hsieh, M.A. Information Theoretic Source Seeking Strategies for Multiagent Plume Tracking in Turbulent Fields. Journal of Marine Science and Engineering 2017, 5, 3

The authors wish to correct the Acknowledgments section in their paper [1] as follows: [...

Concentration and mass deposition measurements in two-phase jet flow with applications to railroad friction management systems

This work presents initial results of a new method to apply friction modifier materials for railroad applications along with a novel particle concentration measurement method for two-phase flows. Until now, railroad friction management systems used liquid friction modifiers or solid sticks to apply the material to the top of the rail or to a moving train’s wheel to reduce the friction. We investigate in lab experiments a new method of applying solid lubricant powders such as molybdenum disulfide (MoS2) and graphite directly on top of the rail using electrostatic powder coating. To design and assess the performance of an applicator for spray or powder coating, it is useful to know the particle concentration in the particle jet. The concentration distribution data will aid in modifying the design of the applicator to achieve the desired deposition pattern. Current methods of concentration measurements such as laser Doppler anemometry (LDA)/phase Doppler anemometry (PDA) and planar nephelometry are excellent to provide accurate local measurements of concentration but are expensive and complicated to set up and operate. Our proposed measurement method is based on light extinction and is much easier to set up and use. This method is capable of providing particle concentration statistics for axisymmetric distributions. We show that the extinction efficiency measured with this method for a given particle agrees with known values (of somewhat less than two) for a non-ideal imaging setup. Furthermore, we demonstrate that the concentration distribution of a jet at the exit of a pipe nozzle as well as downstream is similar to that observed by previous researchers. We also present data on the deposition efficiency of electrostatic powder coating for railroad friction management systems under different test conditions. The results show that applying pure MoS2 or graphite achieves low deposition efficiencies and these materials should be surface treated with a non-conductive coating before being applied. We also discuss how the newly developed particle concentration measurement method can be used to design and monitor the performance of the new railroad friction modifier applicator.Applied Science, Faculty ofMechanical Engineering, Department ofGraduat

Information Theoretic Source Seeking Strategies for Multiagent Plume Tracking in Turbulent Fields

We present information theoretic search strategies for single and multi-robot teams to localize the source of biochemical contaminants in turbulent flows. The robots synthesize the information provided by sporadic and intermittent sensor readings to optimize their exploration strategy. By leveraging the spatio-temporal sensing capabilities of a mobile sensing network, our strategies result in control actions that maximize the information gained by the team while minimizing the time spent localizing the biochemical source. By leveraging the team’s ability to obtain simultaneous measurements at different locations, we show how a multi-robot team is able to speed up the search process resulting in a collaborative information theoretic search strategy. We validate our proposed strategies in both simulations and experiments

Guaranteed Consensus In Radar Deception With A Phantom Track

Radar deception problems serve as a motivation to address the key issue of feasibility in trajectory planning for constrained dynamics of multi-agent systems. In a recent paper, Jayasuriya et al. presents an algorithm which claims to produce a dynamically feasible reference trajectory in real time. However, there was no proof provided for the proposed control strategy. This paper work through that algorithm; and, with a slight modification, provides some conditions on configuration parameters and the desired trajectory such that the proposed control guarantees consensus. These conditions dictate certain conditions on the initial configuration of the agents, consistent with the limitations on their actuators. Simulations support the idea that if the initial configuration along the final team goal is in admissible regions, the agents would always reach a consensus and maintain the formation. Copyright © 2013 by ASME