MODELING AND IMPLEMENTATION OF FEED-FORWARD CONTROL SCHEMES FOR FLEXIBLE ROBOTIC SYSTEMS

Аннотация

INTRODUCTION particularly when high-speed operation or delicate The use of flexible robotic systems, particularly manipulation is required. flexible manipulators, has become increasingly prominent in various industrial, medical, and To mitigate the effects of flexibility and vibration, research applications due to their ability to handle advanced control techniques must be delicate tasks and navigate complex environments. implemented. Feed-forward control schemes have However, the inherent flexibility of these systems shown promise as an effective method for poses significant challenges in achieving high- improving the performance of flexible robotic precision control. Unlike rigid robotic systems, systems. Unlike feedback control, which reacts to flexible manipulators exhibit deflections, system errors, feed-forward control anticipates vibrations, and oscillations during operation, these errors and compensates for them before they which can degrade their accuracy, response time, occur. This preemptive correction allows for and overall performance. These dynamics often smoother motion and more precise positioning, lead to errors that are difficult to correct in real- which is crucial in applications where flexibility- time with traditional feedback control approaches, induced disturbances could compromise task https://www.theamericanjournals.com/index.php/tajet 1 THE USA JOURNALS THE AMERICAN JOURNAL OF ENGINEERING AND TECHNOLOGY (ISSN – 2689-0984) VOLUME 06 ISSUE12 outcomes. rigid-body motion and the flexible deformations that occur during operation. The manipulator’s The key to successful implementation of feed- flexibility is typically represented using beam forward control lies in accurately modeling the theory or finite element analysis (FEA), with the dynamics of the flexible manipulator. A flexible link treated as a series of rigid segments comprehensive model that accounts for both the interconnected by springs and dampers that model rigid-body and flexible deformations is essential the deformation. The model incorporates the mass for predicting the system’s behavior and designing distribution, damping effects, and stiffness effective control strategies. This study focuses on properties of the manipulator, and is expressed in the modeling and implementation of feed-forward the form of partial differential equations (PDEs) control schemes specifically tailored for flexible that govern the system's behavior. robotic manipulators. By incorporating the dynamics of flexibility into the control algorithms, To simplify the modeling, the system is often the aim is to reduce vibration and improve discretized using methods like the finite difference precision in robotic manipulation tasks. method (FDM) or the assumed mode method (AMM), which reduces the PDEs to a set of ordinary This work presents a dynamic model of a flexible differential equations (ODEs). These equations manipulator, which is then used to design and describe the motion of both the end-effector and implement a feed-forward control scheme. The the flexible components of the manipulator. The effectiveness of the control strategies is validated rigid-body dynamics are typically modeled using through experimental results, showcasing the Newton-Euler equations, while the flexible improvements in system performance. Through dynamics are treated using the linearized this study, we aim to demonstrate that feed- equations derived from the beam theory or modal forward control can significantly enhance the analysis. performance of flexible robotic systems, offering a promising approach to addressing the challenges This dynamic model provides the foundation for of flexibility and vibration in high-precision tasks. designing the feed-forward control schemes, as it enables the prediction of flexible deformations and