ARC Researchers at the
56th IEEE Conference on Decision and Control
(December 12-15, 2017 in Melbourne, Australia)

ARC researchers (principal investigators in bold) will be presenting their latest research developments. Below are their papers which may include non-ARC funded research (paper titles in bold are ARC funded).

Agent-Based Systems I
TuA11
Tuesday, December 12, 2017
Paper TuA11.2
10:20-10:40 a.m.
Persistent Coverage of a Two-Dimensional Manifold Subject to Time-Varying Disturbances
William Bentz, Dimitra Panagou (University of Michigan)
Abstract: This paper presents a persistent coverage algorithm for multiple agents subject to 3-D rigid body kinematics. Each agent uses a forward-facing sensing footprint, modeled as an anisotropic spherical sector, to cover a 2-D manifold. The manifold is subject to continual collisions by high speed particles. Particle trajectories are estimated online with an extended Kalman filter using noisy spherical coordinate position measurements. Predicted impact points for each particle, along with associated covariances, are used to generate normally distributed coverage decay. This directs agents to explore in the vicinity of both future and past impact points. The efficacy of the algorithm is demonstrated through simulation.
Paper TuA11.5
11:20-11:40 a.m.
Distributed Multi-Task Formation Control under Parametric Communication Uncertainties
Dongkun Han, Dimitra Panagou (University of Michigan)
(partially ARC funded)
Abstract: Formation control is a key problem in the coordination of multiple agents. It arises new challenges to traditional formation control strategy when the communication among agents is affected by uncertainties. This paper considers the robust multi-task formation control problem of multiple non-point agents whose communications are disturbed by uncertain parameters. The control objectives include 1. achieving the desired configuration; 2. avoiding collisions; 3. preserving the connectedness of uncertain topology. To achieve these objectives, first, a condition of Linear Matrix Inequality (LMI) is proposed for checking the connectedness of an uncertain communication topology. Then, by preserving the initial topological connectedness, a gradient-based distributed controller is designed via Lyapunov-like barrier functions. Two numerical examples illustrate the effectiveness of the proposed method.
 

Stability of Nonlinear Systems II
TuB17
Tuesday December 12, 2017

Paper TuB17.4
14:30-14:50 p.m.

Chebyshev Approximation and Higher Order Derivatives of Lyapunov Functions for Estimating the Domain of Attraction
Dongkun Han, Dimitra Panagou (University of Michigan)
(partially ARC funded)

Abstract: This paper considers dynamic coverage control of unicycle multi-agent systems under power constraints. The agents under consideration model a visually based patrol protocol. They observe their environment via forward-facing conical anisotropic sensing regions. A local coverage control strategy is presented that allows for the cooperative search of a domain while maintaining collision avoidance guarantees using a novel control method based on the coverage level. Additionally, a novel energy-aware global coverage technique is introduced that restricts the operating range of power- constrained agents while shifting the network redistribution effort onto less constrained agents. The results of several scenarios are presented in simulation to illustrate the efficacy of these algorithms.
 

Autonomous Systems
TuC09
Tuesday December 12, 2017

Paper TuC09.1
16:00-16:20 p.m.

Control Strategies for Multiplayer Target-Attacker-Defender Differential Games with Double Integrator Dynamics
Mitchell Coon, Dimitra Panagou (University of Michigan)

Abstract− This paper presents a method for deriving optimal controls and assigning attacker-defender pairs in a target-attacker- defender differential game between an arbitrary numbers of attackers and defenders, all of which are modeled using double integrator dynamics. It is assumed that each player has perfect information about the states and controls of the players within a certain range of themselves, but they are unaware of any players outside of this range. Isochrones are created based on the time-optimal trajectories needed for the players to reach any point in the shortest possible time. The intersections of the players' isochrones are used to determine whether a defender can intercept an attacker before the attacker reaches the target. Sufficient conditions on the detection range of the defenders and the guaranteed capture despite perturbations of the attackers off the nominal trajectories are derived. Then, in simulations with multiple players, attacker-defender pairs are assigned so that the maximum number of attackers are intercepted in the shortest possible time.
 

Emerging Control Applications
WeB07
Wednesday December 13, 2017

Paper WeB07.6
15:10-15:30 p.m.

Iterative Learning-Based Waypoint Optimization for Repetitive Path Planning, with Application to Airborne Wind Energy Systems
Mitchell Cobb1, Kira Barton3, Hosam K. Fathy2, Christopher Vermillion1
1U. of N. Carolina at Charlotte, 2Penn State, 3U. of Michigan
(not ARC funded)

Abstract− This paper presents an iterative learning approach for optimizing waypoints in repetitive path following applications. Our proposed algorithm consists of two key features: First, a recursive least squares fit is used to construct an estimate of the behavior of the performance index. Secondly, an iteration-to-iteration waypoint adaptation law is used to update waypoints in the direction of optimal performance. This waypoint update law parallels the mathematical structure of a traditional iterative learning control (ILC) update but replaces the tracking error term with an error between the present and estimated optimal waypoint sequences. The proposed methodology is applied to the crosswind path optimization of an airborne wind energy (AWE) system, where the goal is to maximize the average power output over a figure-8 path. In validating the tools from this work, we introduce a simplified 2-dimensional analog to the more complex 3-dimensional AWE system, which distills the problem to its core elements. Using this model, we demonstrate that the proposed waypoint adaptation strategy successfully achieves convergence to near-optimal figure-8 paths for a variety of initial conditions.
 

Cooperative Control II
WeC11

Wednesday December 13, 2017

Paper WeC11.3
16:40-17:00 p.m.

Robust Semi-Cooperative Multi-Agent Coordination in the Presence of Stochastic Disturbances
Kunal Garg, Dongkun Han, Dimitra Panagou (University of Michigan)
(partially ARC funded)

Abstract− This paper presents a robust distributed coordination protocol that achieves generation of collision-free trajectories for multiple unicycle agents in the presence of stochastic uncertainties. We build upon our earlier work on semi-cooperative coordination and we redesign the coordination controllers so that the agents counteract a class of state (wind) disturbances and measurement noise. Safety and convergence is proved analytically, while simulation results demonstrate the efficacy of the proposed solution.
 

Energy Systems
ThA06

Thursday December 14, 2017

Paper ThA06.4
11:00-11:20 a.m.

Comparing Optimal Battery Warm-Up Strategies Based on Self-Heating
Shankar Mohan, Anna G. Stefanopoulou (University of Michigan)

Abstract− The ability of Lithium-ion batteries to perform work decreases at low temperature of operation; a common strategy to improve their productivity is to warm them. In our recent works we have raised the need to study the energy-optimal warm-up of batteries. More recently, our work used battery temperature to determine if the battery has warmed up. The power capability of batteries is a more relatable and arguably useful means to terminate the warm-up process. This work builds upon its predecessors by using power capability as stopping condition, analyzes the problem and numerically solves the same. Subsequently, the relation between the minimum-time and minimum-energy warm-up problem formulations that employ temperature and power constraints to terminate warm-up are theoretically established.
 

Applications of Graph Theory
ThB04

Thursday December 14, 2017

Paper ThB04.5
14:50-15:10 p.m.

r-Robustness and (r,s)-Robustness of Circulant Graphs
James Usevitch, Dimitra Panagou (University of Michigan)

Abstract− There has been recent growing interest in graph theoretical properties known as r- and (r,s)-robustness. These properties serve as sufficient conditions guaranteeing the success of certain consensus algorithms in networks with misbehaving agents present. Due to the complexity of determining the robustness for an arbitrary graph, several methods have previously been proposed for identifying the robustness of specific classes of graphs or constructing graphs with specified robustness levels. The majority of such approaches have focused on undirected graphs. In this paper we identify a class of scalable directed graphs whose edge set is determined by a parameter k and prove that the robustness of these graphs is also determined by k. We support our results through computer simulations.
 

Plenary Lecture
WeP1.1
08:30-09:30, Wednesday December 13, 2017

Control Engineers: The Unsung Heroes of Battery Technology

Anna G. Stefanopoulou
William Clay Ford Professor of Manufacturing, Department of Mechanical Engineering, University of Michigan, USA.

Abstract. The 25th anniversary of the commercialization of lithium-ion batteries marks their wide-spread use in handheld consumer electronics and coincides with a period of intense efforts for powering electric vehicles. Managing the potent brew of lithium ions in the large quantities necessary for vehicle propulsion is anything but straightforward. Designing the complex conductive structure, choosing the electrode material for locking the energy in high potential states and synthesizing the interfaces for releasing the chemical energy at fast but controllable rates has been the focus of the electrochemists and material scientists. But from the Rosetta-Philae spacecraft landing three billion miles away from Earth to the daily commute of a hybrid electric automobile, the control engineers behind the battery management system (BMS) have been the unsung heroes. The BMS is the brain of the battery system and is responsible for State of Charge (SOC), State of Health (SOH) and State of Power (SOP) estimation while protecting the cell by limiting its power. The BMS relies on accurate prediction of complex electrochemical, thermal and mechanical phenomena. This raises the question of model and parameter accuracy. Moreover, if the cells are aging, which parameters should we adapt after leveraging limited sensor information from the measured terminal voltage and sparse surface temperatures? With such a frugal sensor set, what is the optimal sensor placement? To this end, control techniques and novel sensors that measure the cell swelling during lithium intercalation and thermal expansion will be presented. We will conclude by highlighting the fundamental difficulties that keep every battery control engineer awake, namely predicting local hot spots, detecting internal shorts, and managing the overwhelming energy released during a thermal runaway.