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1. Anti-Windup Compensator Design for Guidance and Control of Quadrotors

   https://doi.org/10.23919/ACC60939.2024.10644412  

   Shahbazzadeh, Majid; Richards, Christopher (July 2024, IEEE)

   In this paper, the problem of anti-windup compensator (AWC) design for guidance and control of quadrotors in an unknown environment is addressed. Quadrotors can be affected by disturbances (such as wind), which potentially result in saturation of the propellers. When saturation occurs, the flight can become unstable, leading to a crash. On the other hand, designing an AWC to mitigate the saturation effects in the control system of a quadrotor can be a challenging task due to the heavy couplings and complex nonlinear dynamics. For this reason, we propose a new structure to design an AWC-based control system to solve this problem. Simulation results are presented in three cases: 1-without saturation, 2-with saturation - without AWC, 3-with saturation - with AWC. The effectiveness of the proposed theoretical results are verified by comparisons. 

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2. Anti-Windup Compensation for Quadrotor Trajectory Tracking With External Disturbances

   https://doi.org/10.1109/LCSYS.2024.3516635  

   Shahbazzadeh, Majid; Richards, Christopher M (December 2024, IEEE Control Systems Letters)

   Tarbouriech, S (Ed.)

   This letter considers the problem of trajectory tracking for quadrotors operating in wind conditions that result in propeller thrust saturation. To address this problem, an anti-windup compensator (AWC) is developed to reduce the tracking performance degradation and destabilizing effects from thrust saturation. Relationships are derived showing how the tracking error and AWC states are influenced by the wind disturbance and saturation, and how the influences depend on the controller and AWC gains. As a result, these gains can be tuned to achieve desired performance levels. Simulation results are presented to validate the effectiveness of the proposed method. 

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3. Anti‐windup compensation for model reference adaptive control schemes

   https://doi.org/10.1002/rnc.7511  

   Sofrony, Jorge; Turner, Matthew C; Richards, Christopher M (June 2024, International Journal of Robust and Nonlinear Control)

   Actuator constraints, particularly saturation limits, are an intrinsic and long‐standing problem in the implementation of most control systems. Model reference adaptive control (MRAC) is no exception and it may suffer considerably when actuator saturation is encountered. With this in mind, this paper proposes an anti‐windup strategy for model reference adaptive control schemes subject to actuator saturation. A prominent feature of the proposed compensator is that it has the same architecture as well‐known nonadaptive schemes, namely model recovery anti‐windup, which rely on the assumption that the system model is known accurately. Since, in the adaptive case, the model is largely unknown, the proposed approach uses an “estimate” of the system matrices for the anti‐windup formulation and modifies the adaptation laws that update the controller gains; if the (unknown) ideal control gains are reached, the model recovery anti‐windup formulation is recovered. The main results provide conditions under which, if theidealcontrol signal eventually lies within the control constraints, then the system states will converge to those of the reference model, that is, the tracking error will converge to zero asymptotically. The article deals with open‐loop stable linear systems and highlights the main challenges involved in the design of anti‐windup compensators for model‐reference adaptive control systems, demonstrating its success via a flight control application. 

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4. Hybrid locomotion at the insect scale: Combined flying and jumping for enhanced efficiency and versatility

   https://doi.org/10.1126/sciadv.adu4474  

   Hsiao, Yi-Hsuan; Bai, Songnan; Guan, Zhongtao; Kim, Suhan; Ren, Zhijian; Chirarattananon, Pakpong; Chen, Yufeng (April 2025, Science Advances)

   Insect-scale robots face two major locomotive challenges: constrained energetics and large obstacles that far exceed their size. Terrestrial locomotion is efficient yet mostly limited to flat surfaces. In contrast, flight is versatile for overcoming obstacles but requires high power to stay aloft. Here, we present a hopping design that combines a subgram flapping-wing robot with a telescopic leg. Our robot can hop continuously while controlling jump height and frequency in the range of 1.5 to 20 centimeters and 2 to 8.4 hertz. The robot can follow positional set points, overcome tall obstacles, and traverse challenging surfaces. It can also hop on a dynamically rotating plane, recover from strong collisions, and perform somersaults. Compared to flight, this design reduces power consumption by 64 percent and increases payload by 10 times. Although the robot relies on offboard power and control, the substantial payload and efficiency improvement open opportunities for future study on autonomous locomotion. 

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5. Obstacle-Aided Navigation of a Soft Growing Robot

   Greer, J. D.; Blumenschein, L. H.; Okamura, A. M.; Hawkes, E. W. (May 2018, IEEE International Conference on Robotics and Automation)

   For many types of robots, avoiding obstacles is necessary to prevent damage to the robot and environment. As a result, obstacle avoidance has historically been an im- portant problem in robot path planning and control. Soft robots represent a paradigm shift with respect to obstacle avoidance because their low mass and compliant bodies can make collisions with obstacles inherently safe. Here we consider the benefits of intentional obstacle collisions for soft robot navigation. We develop and experimentally verify a model of robot-obstacle interaction for a tip-extending soft robot. Building on the obstacle interaction model, we develop an algorithm to determine the path of a growing robot that takes into account obstacle collisions. We find that obstacle collisions can be beneficial for open-loop navigation of growing robots because the obstacles passively steer the robot, both reducing the uncertainty of the location of the robot and directing the robot to targets that do not lie on a straight path from the starting point. Our work shows that for a robot with predictable and safe interactions with obstacles, target locations in a cluttered, mapped environment can be reached reliably by simply setting the initial trajectory. This has implications for the control and design of robots with minimal active steering. 

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