@article{naik_beknalkar_reed_mazzoleni_fathy_vermillion_2023, title={Pareto Optimal and Dual-Objective Geometric and Structural Design of an Underwater Kite for Closed-Loop Flight Performance}, volume={145}, ISSN={["1528-9028"]}, DOI={10.1115/1.4055978}, abstractNote={Abstract}, number={1}, journal={JOURNAL OF DYNAMIC SYSTEMS MEASUREMENT AND CONTROL-TRANSACTIONS OF THE ASME}, author={Naik, Kartik and Beknalkar, Sumedh and Reed, James and Mazzoleni, Andre and Fathy, Hosam and Vermillion, Chris}, year={2023}, month={Jan} }
 @article{haydon_reed_vermillion_2023, title={Persistent Mission Planning of an Energy-Harvesting Autonomous Underwater Vehicle for Gulf Stream Characterization}, ISSN={["1558-0865"]}, DOI={10.1109/TCST.2023.3328105}, abstractNote={Characterizing evolving ocean environments is important to scientific, renewable energy, and military applications. However, performing meaningful characterizations of these resources is complicated by their spatiotemporal evolution and partial observability. In this work, we specifically consider the use of an autonomous underwater vehicle (AUV) with a deployable energy-harvesting kite that enables persistent missions. When the AUV parks itself on the seabed, the kite can deploy, harvesting significant amounts of energy through periodic figure-8 flight. Focusing on a Gulf Stream observational mission, we present a persistent planning algorithm that fuses Gaussian process (GP) modeling with model predictive control (MPC) to optimize AUV charging times to maximize the informativeness of the mission. Based on simulation studies using a mid-Atlantic bight, south Atlantic bight regional ocean model (MAB-SAB-ROM), we demonstrate a 20% reduction in the time required to traverse a given section of the Gulf Stream, which leads to a significant reduction in prediction error.}, journal={IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY}, author={Haydon, Benjamin and Reed, James and Vermillion, Christopher}, year={2023}, month={Nov} }
 @article{reed_abney_mishra_naik_perkins_vermillion_2023, title={Stability and Performance of an Undersea Kite Operating in a Turbulent Flow Field}, volume={31}, ISSN={["1558-0865"]}, DOI={10.1109/TCST.2023.3237614}, abstractNote={In this article, we examine the effects of flow disturbances resulting from turbulence on the dynamic behavior of an underwater energy-harvesting kite system that executes periodic figure-8 flight. Due to the periodic nature of the kite’s operation, we begin by assessing orbital stability using the Floquet analysis and stroboscopic intersection analysis of a Poincaré section, with the former analysis performed on a simplified “unifoil” model and the latter performed on a six-degree-of-freedom (6-DOF)/flexible tether model. With periodic stability established, a frequency-domain analysis based on a linearization about the kite’s path is used to predict the quality of flight path tracking as a function of the turbulence frequency. To validate the accuracy of these simulation-based predictions under flow disturbances, we compare the predictions of the kite’s behavior against the results of small-scale tow testing experiments performed in a controlled pool environment.}, number={4}, journal={IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY}, author={Reed, James and Abney, Andrew and Mishra, Kirti D. and Naik, Kartik and Perkins, Edmon and Vermillion, Chris}, year={2023}, month={Jul}, pages={1663–1678} }
 @article{abney_reed_naik_bryant_herbert_leonard_vadlamannati_mook_beknalkar_alvarez_et al._2022, title={Autonomous Closed-Loop Experimental Characterization and Dynamic Model Validation of a Scaled Underwater Kite}, volume={144}, ISSN={["1528-9028"]}, DOI={10.1115/1.4054141}, abstractNote={Abstract}, number={7}, journal={JOURNAL OF DYNAMIC SYSTEMS MEASUREMENT AND CONTROL-TRANSACTIONS OF THE ASME}, author={Abney, Andrew and Reed, James and Naik, Kartik and Bryant, Samuel and Herbert, Dillon and Leonard, Zak and Vadlamannati, Ashwin and Mook, Mariah and Beknalkar, Sumedh and Alvarez, Miguel and et al.}, year={2022}, month={Jul} }
 @article{cobb_reed_wu_mishra_barton_vermillion_2022, title={Flexible-Time Receding Horizon Iterative Learning Control With Application to Marine Hydrokinetic Energy Systems}, ISSN={["1558-0865"]}, DOI={10.1109/TCST.2022.3165734}, abstractNote={This brief presents an iterative learning control (ILC) framework for a class of repetitive control (RC) applications characterized by: 1) continuous operation; 2) flexible iteration time; and 3) an economic performance metric. Specifically, the effect of iteration-varying initial conditions, resulting from the continuous nature of the operation, is accounted for through an iteration domain receding horizon formulation. To address the need for flexible iteration times, the time-domain dynamics are transformed into path-domain dynamics characterized by a non-dimensional parameter spanning an iteration-invariant range. The resulting model is used to derive learning filters that minimize a multi-objective economic cost. The proposed methodology is applied to the control a kite-based marine hydrokinetic (MHK) system, which executes high-speed, repetitive flight paths with the objective of maximizing its lap-averaged power output. The proposed approach is validated via simulations of a medium-fidelity nonlinear model of a kite-based MHK system, and the results demonstrate robust and fast convergence of the kite to power-optimal flight patterns.}, journal={IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY}, author={Cobb, Mitchell and Reed, James and Wu, Maxwell and Mishra, Kirti D. and Barton, Kira and Vermillion, Chris}, year={2022}, month={Apr} }
 @article{mishra_reed_wu_barton_vermillion_2021, title={Hierarchical Structures for Economic Repetitive Control}, ISSN={["0743-1546"]}, DOI={10.1109/CDC45484.2021.9683000}, abstractNote={For many emerging repetitive control applications such as wind and marine energy generation systems, gait-cycle following in legged locomotion, remote sensing, surveillance, and reconnaissance, the primary objective for repetitive control (RC) is optimization of a cycle cost such as the lap-averaged power generated and metabolic cost of locomotion, as opposed to the classical requirement of tracking a known reference trajectory by the system output. For this newer class of applications, only a range of reference trajectories suitable for cyclic operation is known a priori, the range potentially encapsulating various operational constraints, and as part of repetitive control, it is desired that over a number of operation cycles, the cycle cost, or the economic metric, is optimized. With this underlying motivation, a hierarchical solution is presented, wherein the inner loop includes a classical repetitive controller that tracks a reference trajectory of known period, and the outer loop iteratively learns the desired reference trajectory using a combination of the system and cost function models and the measured cycle cost. This approach results in optimum steady-state cyclic operation. A steepest descent type algorithm is used in the outer loop, and via Lyapunov-like arguments, the existence of tuning parameters resulting in robust and optimal steady-state cyclic operation is discussed. Appropriate guidelines for parameter tuning are presented, and the proposed method is numerically validated using an example of an inverted pendulum.}, journal={2021 60TH IEEE CONFERENCE ON DECISION AND CONTROL (CDC)}, author={Mishra, Kirti D. and Reed, James and Wu, Maxwell and Barton, Kira and Vermillion, Chris}, year={2021}, pages={5838–5844} }
 @article{cobb_reed_daniels_siddiqui_wu_fathy_barton_vermillion_2021, title={Iterative Learning-Based Path Optimization With Application to Marine Hydrokinetic Energy Systems}, ISSN={["1558-0865"]}, DOI={10.1109/TCST.2021.3070526}, abstractNote={This article presents an iterative learning control (ILC)-based approach for optimizing the flight path geometry of a tethered marine hydrokinetic (MHK) energy system. This type of system, which replaces the tower of a conventional system with a tether and a lifting body, can capture energy either through an on-board rotor or by driving a generator with tension in the tether. In the latter mode of operation, which represents the focal point of this effort, net positive energy is generated over one cycle of high-tension spool-out followed by low-tension spool-in. Because the net energy generation is sensitive to the shape of the flown path, we employ an iterative learning update law to adapt the path shape from one lap to the next. This update law is complemented with an iterative power take-off (PTO) controller, which adjusts the spooling profile at each iteration to ensure zero net spooling. We present and validate the proposed control approach in both uniform and spatiotemporally varying turbulent flow environments, based on a realistic ocean model detailed in this article. Finally, based on simulation results across a wide range of excitation levels, we perform a simulation-based assessment of convergence properties, comparing these results against bounds derived in the authors’ prior work.}, journal={IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY}, author={Cobb, Mitchell and Reed, James and Daniels, Joshua and Siddiqui, Ayaz and Wu, Max and Fathy, Hosam and Barton, Kira and Vermillion, Chris}, year={2021}, month={Apr} }
 @article{reed_wu_barton_vermillion_mishra_2021, title={Library-Based Norm-Optimal Iterative Learning Control}, ISSN={["0743-1546"]}, DOI={10.1109/CDC45484.2021.9682812}, abstractNote={This paper presents a new iterative learning control (ILC) methodology, termed library-based norm-optimal ILC, which optimally accounts for variations in measurable disturbances and plant parameters from one iteration to the next. In this formulation, previous iteration-varying disturbance and/or plant parameters, along with the corresponding control and error sequences, are intelligently maintained in a dynamically evolving library. The library is then referenced at each iteration, in order to base the new control sequence on the most relevant prior iterations, according to an optimization metric. In contrast with the limited number of library-based ILC methodologies pursued in the literature, the present work (i) selects provably optimal interpolation weights, (ii) presents methods for starting with an empty library and intelligently truncating the library when it becomes too large, and (iii) demonstrates convergence to an optimal performance value. To demonstrate the effectiveness of our new methodology, we simulate our library-based norm-optimal ILC method on a linear time-varying model of a micro-robotic deposition system.}, journal={2021 60TH IEEE CONFERENCE ON DECISION AND CONTROL (CDC)}, author={Reed, James and Wu, Maxwell and Barton, Kira and Vermillion, Chris and Mishra, Kirti D.}, year={2021}, pages={5851–5857} }
 @article{reed_cobb_daniels_siddiqui_muglia_vermillion_2020, title={Hierarchical Control Design and Performance Assessment of an Ocean Kite in a Turbulent Flow Environment}, volume={53}, ISSN={["2405-8963"]}, DOI={10.1016/j.ifacol.2020.12.1887}, abstractNote={This paper presents a hierarchical control framework for a kite-based marine hydrokinetic (MHK) system that executes power-augmenting cross-current flight, along with simulation results based on a high-fidelity turbulent flow model that is representative of flow conditions in the Gulf Stream. The hierarchical controller is used to robustly regulate both the kite’s flight path and the intra-cycle spooling behavior, which is ultimately used to realize net positive energy production at a base station motor/generator system. Two configurations are examined in this paper: one in which the kite is suspended from a surface-mounted platform, and another in which the kite is deployed from the seabed. To evaluate the robustness of this control framework in a realistic ocean environment, we present simulation results whereby we superimpose low-frequency data from the Mid Atlantic Bight South Atlantic Bight Regional Ocean Modeling System and acoustic Doppler current profiler measurements with a high-frequency turbulence model, resulting in a high-fidelity 3D spatiotemporal flow field that is presented to the kite system. Based on this simulation framework, we demonstrate the effectiveness of the control system both in terms of robust flight and power generation.}, number={2}, journal={IFAC PAPERSONLINE}, author={Reed, James and Cobb, Mitchell and Daniels, Joshua and Siddiqui, Ayaz and Muglia, Michael and Vermillion, Chris}, year={2020}, pages={12726–12732} }
 @article{daniels_reed_cobb_siddiqui_vermillion_2020, title={Optimal Cyclic Spooling Control for Kite-Based Energy Systems}, volume={53}, ISSN={["2405-8963"]}, DOI={10.1016/j.ifacol.2020.12.1883}, abstractNote={This paper presents a control strategy for optimizing the the spooling speeds of tethered energy harvesting systems that generate energy through cyclic spooling motions which consist of high-tension spool-out and low-tension spool-in. Specifically, we fuse continuous-time optimal control tools, including Pontryagin’s Maximum Principle, with an iteration domain co-state correction, to develop an optimal spooling controller for energy extraction. In this work, we focus our simulation results specifically on an ocean kite system where the goal is to optimize the spooling profile while remaining at a consistent operating depth and corresponding average tether length. This paper demonstrates a 14-45% improvement (depending on the operating tether length and environmental flow speed) in power generation compared to a baseline, heuristic, control strategy.}, number={2}, journal={IFAC PAPERSONLINE}, author={Daniels, Joshua and Reed, James and Cobb, Mitchell and Siddiqui, Ayaz and Vermillion, Chris}, year={2020}, pages={12719–12725} }