Soumya Ranjan Sahoo

The underactuation of conventional aerial vehicles limits their ability to independently control position and attitude, motivating the use of overactuated designs such as tilt-rotor quadrotors. Existing works on tilt-rotor quadrotors primarily focus on determining the minimum thrust-to-weight ratio required for hovering at arbitrary orientations. However, they do not address the maximum allowable attitude range within which independent control is feasible given specific thrust constraints. In this work, we investigate the feasible attitude range within which a tilt-rotor quadrotor can maintain independent control, given rotor thrust limits. First, we formulate the thrust constraints as convex functions and solve them using convex optimization techniques to identify feasible sets. To determine the maximum attitude that allows for independent control under thrust constraints, we pose a nonconvex optimization problem and employ a successive convex approximation (SCA) technique to compute a optimal solution, which corresponds to the optimal solution of the original nonconvex problem. Given the maximum attitude limits, we then compute the minimum thrust required per rotor to achieve independent control. Furthermore, we determine the maximum allowable disturbance magnitude that the tilt-rotor quadrotor can handle while retaining independent control. The study results are verified through processor-in-the-loop (PIL) simulations and outdoor hardware experiments on a tilt-rotor quadrotor. An illustrative video showing both the PIL simulation and hardware experimental results can be found at: https://youtu.be/6qjc9_KtACM.

Integration of Renewable Energy Sources (RES) prompts a need for increased grid flexibility. While Optimal Transmission Switching (OTS) harnesses this flexibility, deterministic OTS fails to provide optimal topology for injection uncertainties from loads and RESs. This paper presents a novel two-level, three-stage formulation for robust AC OTS (ACOTS), addressing injection uncertainties in the day-ahead operation of power networks. Unlike previous formulations, the proposed model has no approximations of power flow equations. The master problem is a Mixed Integer Linear Programming (MILP) formulation that determines robust optimal network topology, serving as input to slave problems. The slave problems are solved sequentially, where the first slave is a deterministic AC Optimal Power Flow (ACOPF) problem, and the second slave unveils worst-case uncertainty, thereby co-optimizing dispatch in the considered uncertainty range. The proposed formulation is solved by Generalized Benders decomposition, which is devised with an accelerated convergence technique. Consideration of budget of uncertainty constraints reduces conservatism of optimal topology. Validation through Monte-Carlo Simulation-based ACOPF, appended with load curtailment, demonstrates the setpoints' robustness on NESTA and South Carolina 500 bus systems. Comparison with previous approaches and the Column-and-Constraint Generation Generation (C&CG) algorithm underscores the proposed model's effectiveness in achieving a robust optimal network topology.

The series stacked active power decoupling (SS-APD) circuit is a power dense and efficient alternative for ripple energy storage in single phase power converter. The SS-APD circuit needs to absorb a small amount of real power to meet power losses in it. For this, the literature uses additional power supply or modifies the controller for SS-APD circuit. Such modified controllers require high bandwidth current sensing or noise-prone differentiation function. To address these challenges, this paper proposes a conductance emulation control for SS-APD circuit. Here, the value of emulated conductance dictates the real power absorbed by the SS-APD circuit. It eliminates the need for differentiation function, dc-link current sensing and additional power supply for absorbing real power. Further, it uses feedback of dc-link voltage and enables independent control of SS-APD circuit from the single-phase converter. The proposed technique is investigated using state-plane analysis and small signal impedance analysis to highlight the design dependencies. In addition, the practical challenges such as proper sensing of ripple in dc-link voltage are also addressed. The load transient and steady-state performance of the proposed technique are validated by experimental studies with a 2 kW laboratory prototype.

This paper addresses the challenge of velocity control in fixed canard decoupled dual-spin projectiles, focusing on the nonlinearities and parameter uncertainties of the system. A motor-generator test bench and a dynamical model are developed to emulate the dual-spin system accurately, enabling thorough experimentation and analysis. Robust control strategies, specifically sliding mode control and super-twisting control, are implemented and compared against traditional linear PI, PID, and nonlinear dynamic inversion controllers. Performance evaluations are conducted through two experiments: first, tracking a step reference speed with a fixed driving speed, and second, replicating real-world dual-spin behavior by tracking a variable speed trajectory with varying driving speeds. Results demonstrate that the super-twisting controller and PID controller outperform other strategies, exhibiting minimal reaching time and lower steady-state error during both step reference and disturbance tests.

In the existing literature on the robust control design of UAV systems, the controllers are designed without considering motor dynamics. Hence, if these controller gains are not correctly tuned, the system undergoes oscillation and may even go unstable. We have demonstrated this through an experiment in this work. Here, we propose a novel control strategy that considers actuator parameter uncertainties, including motor dynamics for a tilt quadrotor. This strategy is based on the traditional two-loop control scheme where the inner loop controls the angular velocity, and the outer loop controls the vehicle’s attitude based on quaternions. In the quaternion-based controller, usually, the convergence rate increases when the quaternion starts closer to its equilibrium point, thus making it challenging to design a linear controller for the inner loop. To overcome this, we propose a nonlinear control with a varying gain for the outer loop that ensures the quaternion has a fixed convergence rate. We propose the control design of the inner loop, which consists of a disturbance observer (DOB) and a linear controller. The DOB is optimally designed to minimize external disturbances in the presence of model uncertainties. With the DOB, a linear controller is designed for the inner loop, guaranteeing robust stability and performance against the model and actuator parameter uncertainties. The results of experimental flights are reported in this paper, and the corresponding videos are at https://youtu.be/dS9WUR0yLhA. Note to Practitioners —This paper was motivated by the potential application of the tilt quadrotors in industry, such as surveillance in confined spaces and landing on high-speed moving targets, due to their independent control of position and orientation. We demonstrate that a controller designed without consideration of motor dynamics can result in unwanted oscillatory or unstable behaviour in the case of a UAV. So, the proposed method considers these dynamics during the design. In most of the existing control designs based on quaternion, the convergence rate depends on the initial condition. This paper proposes a nonlinear control with a varying gain to achieve a faster response that ensures the quaternion has a fixed convergence rate. The stability and convergence of this nonlinear controller are analyzed mathematically and validated through experiments. In UAVs, the precise moment-of-inertia and motor parameters are difficult to estimate, and external disturbances such as wind gusts are always present in outdoor environments. Therefore, this paper designs a robust control scheme which guarantees robust stability and performance against inertia and motor parameter uncertainties. Secondly, a disturbance observer (DOB) whose filter coefficient is optimally tuned such that the effect of external disturbance is minimized in the presence of model uncertainties. The proposed approach is validated on a tilt quadrotor in an outdoor environment and has a faster response than the existing ones having same maximum convergence rate. Thus, this proposed approach has potential applications, like landing a tilt quadrotor on a ship while the ship is in motion under the influence of waves and winds.

Battery energy storage system (BESS), as grid forming unit, can quickly regulate voltage and frequency for a 100% inverter-based islanded low voltage microgrid. However, due to some inherent characteristics of this network, such as: (a) coupling among voltage and frequency dynamics, (b) dynamics of dc source, and (c) timescale coupling among converter and network, small-signal stability is a major concern. This paper proposes an adaptive feed-forward compensation scheme for each BESS unit to reduce dynamic interactions among converters and network/load parameters. Additionally, the proposed scheme can enhance system damping capability for a wide range of operating conditions without the need for any prior/ continuous generation/network information or additional sensors. This technique can preserve the voltage/frequency regulation capability of the traditional (ω − P/V − Q) droop control scheme for any low voltage networks. The existing small-signal model is modified to include dc-source, dc link, and proposed feed-forward dynamics, which assists in analyzing the impact of dc-side, acside, and network parameters on system small-signal stability. The system performance is analyzed with extensive case studies conducted on a CIGRE TF C6 : 04 : 02 benchmark system. The proposed model is validated using a real-time digital simulator with hardware-in-loop setup