@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 This paper presents the formulation and results for a control-aware optimization of the combined geometric and structural design of an energy-harvesting underwater kite. Because kite-based energy-harvesting systems, both airborne and underwater, possess strong coupling between closed-loop flight control, geometric design, and structural design, consideration of all three facets of the design within a single codesign framework is highly desirable. However, while prior literature has addressed one or two attributes of the design at a time, this work constitutes the first comprehensive effort aimed at addressing all three. In particular, focusing on the goals of power maximization and mass minimization, we present a codesign formulation that fuses a geometric optimization tool, structural optimization tool, and closed-loop flight efficiency map. The resulting integrated codesign tool is used to address two mathematical optimization formulations that exhibit subtle differences: a Pareto optimal formulation and a dual-objective formulation that focuses on a weighted power-to-mass ratio as the techno-economic metric of merit. Based on the resulting geometric and structural designs, using a mediumfidelity closed-loop simulation tool, the proposed formulation is shown to achieve more than three times the powerto-mass ratio of a previously published, unoptimized benchmark design.}, 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{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 This paper presents the closed-loop experimental framework and dynamic model validation for a 1/12-scale underwater kite design. The pool-based tow testing framework described herein, which involves a fully actuated, closed-loop controlled kite and flexible tether, significantly expands upon the capabilities of any previously developed open-source framework for experimental underwater kite characterization. Specifically, the framework has allowed for the validation of three closed-loop flight control strategies, along with a critical comparison between dynamic model predictions and experimental results. In this paper, we provide a detailed presentation of the experimental tow system and kite setup, describe the control algorithms implemented and tested, and quantify the level of agreement between our multi-degree-of-freedom kite dynamic model and experimental data. We also present a sensitivity analysis that helps to identify the most influential parameters to kite performance and further explain the remaining mismatches between the model and data.}, 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={Abstract 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={Abstract 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} }