Browsing by Subject "Inverse dynamics"

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Open Access
Control of underactuated planar pronking through an embedded spring-mass Hopper template
(2011) Ankaralı, M.M.; Saranlı, U.
Autonomous use of legged robots in unstructured, outdoor settings requires dynamically dexterous behaviors to achieve sufficient speed and agility without overly complex and fragile mechanics and actuation. Among such behaviors is the relatively under-studied pronking (aka. stotting), a dynamic gait in which all legs are used in synchrony, usually resulting in relatively slow speeds but long flight phases and large jumping heights. Instantiations of this gait for robotic systems have been mostly limited to open-loop strategies, suffering from severe pitch instability for underactuated designs due to the lack of active feedback. However, both the kinematic simplicity of this gait and its dynamic nature suggest that the Spring-Loaded Inverted Pendulum model (SLIP) would be a good basis for the implementation of a more robust feedback controller for pronking. In this paper, we describe how template-based control, a controller structure based on the embedding of a simple dynamical "template" within a more complex "anchor" system, can be used to achieve very stable pronking for a planar, underactuated hexapod robot. In this context, high-level control of the gait is regulated through speed and height commands to the SLIP template, while the embedding controller ensures the stability of the remaining degrees of freedom. We use simulation studies to show that unlike existing open-loop alternatives, the resulting control structure provides explicit gait control authority and significant robustness against sensor and actuator noise. © 2010 Springer Science+Business Media, LLC.
Open Access
Learning based control compensation for multi-axis gimbal systems using inverse and forward dynamics
(2021-09) Leblebicioğlu, Damla
Unmanned aerospace vehicles (such as rockets, drones, and satellites) usually carry sensors as their primary payload. These sensors (i.e., electro-optical and/or infrared imaging cameras) are used for image processing, target tracking, surveillance, mapping, and providing high-resolution imagery for environmental surveys. It is crucial to obtain a steady image in all of those applications. This is typically accomplished by using multi-axis gimbal systems. This study concentrates on the modeling and control of a multi-axis gimbal system that will be mounted on a surface-to-surface tactical missile. A novel and fully detailed procedure is proposed to derive the nonlinear and highly coupled EOMs (Equations of Motion) of the two-axis gimbal system. Different from the existing works, Forward Dynamics of the two-axis gimbal system is modeled using multi-body dynamics modeling techniques. In addition to Forward Dynamics model, Inverse Dynamics model is generated to estimate the complementary torques associated with the state and mechanism-dependent, complex disturbances acting on the system. Forward and Inverse Dynamics models are used in Monte Carlo Simulations (MCSs) for Sensitivity Analysis. A multilayer perceptron (MLP) structure based disturbance compensator is implemented to cope with external and internal disturbances and parameter uncertainities through torque input channel. Comparisons with well known controllers such as cascaded PID, ADRC (Active Disturbance Rejection Control), Inverse Dynamics based controllers show that the NN (neural network)-based controller is more succesful in the full operational range without requiring any tuning or adjustment. Implementation of MLP assisted closed-loop control with simulations using Simulink® are performed. Finally, proposed control algorithms are tested on the physical system by using Simulink® Real-Time (xPC Target). Comparative results are presented in figures and tables in the thesis.