Enhanced Control of Suspended Cable Robots Using an Optimized Fuzzy Synergetic Method

Аннотация

Suspended Cable-Driven Parallel Robots (CDPRs) are increasingly utilized in various applications due to their large workspace and high payload capacity. However, their control presents significant challenges, including highly nonlinear dynamics, the requirement for positive cable tension, and susceptibility to uncertainties and external disturbances. Traditional control methods often struggle to achieve precise trajectory tracking while ensuring positive cable tension and robustness. This article proposes and analyzes a hypothetical Optimized Adaptive Fuzzy Synergetic Controller (OAFSC) for suspended CDPRs. The controller combines the strengths of synergetic control for robust tracking and dimension reduction, adaptive control for handling uncertainties, and fuzzy logic for approximating complex nonlinearities. Furthermore, the controller parameters are optimized using a meta-heuristic algorithm, specifically the Dragonfly Algorithm (DA), to enhance performance. The Introduction provides background on CDPRs and the motivation for advanced control strategies. The Methods section details the hypothetical design of the OAFSC, the integration of fuzzy logic and adaptive laws, the formulation of the optimization problem, and the application of the DA. Hypothetical Results demonstrate improved trajectory tracking accuracy, enhanced robustness to disturbances and model uncertainties, and effective management of cable tensions compared to conventional control approaches. The Discussion interprets these potential findings, highlights the advantages of the OAFSC, acknowledges limitations of the hypothetical study, and suggests future research directions, including experimental validation and exploration of other optimization techniques. Keywords: Cable-Driven Parallel Robots, Suspended CDPRs, Adaptive Control, Fuzzy Logic Control, Synergetic Control, Optimization, Dragonfly Algorithm, Trajectory Tracking. suspended ones, is a complex task due to several Introduction: Cable-Driven Parallel Robots (CDPRs) inherent challenges. These include highly nonlinear and represent a class of parallel manipulators where the coupled dynamics, the non-negligible effect of cable end-effector (platform) is manipulated by multiple sagging in large workspaces, the need to maintain cables driven by winches, typically located at a base positive tension in all cables to ensure control authority frame [2, 3]. Compared to rigid-link parallel robots, and prevent cable entanglement, and sensitivity to CDPRs offer advantages such as large workspace, high model uncertainties and external disturbances [2, 5]. payload-to-weight ratio, and reconfigurability, making Achieving precise trajectory tracking while them suitable for diverse applications including large- simultaneously satisfying the positive cable tension scale manufacturing, construction, rescue operations, constraint and ensuring robustness against and even landmine detection [1, 3, 21]. Suspended uncertainties is a major focus in CDPR control research CDPRs, where the base frame is above the workspace [5, 6]. and gravity assists in maintaining cable tension, are a common configuration [1, 2]. Various control strategies have been applied to CDPRs, ranging from classical PID control to advanced Despite their advantages, controlling CDPRs, especially American Journal of Applied Science and Technology 1 https://theusajournals.com/index.php/ajast American Journal of Applied Science and Technology (ISSN: 2771-2745) nonlinear and adaptive control methods [4, 5, 6, 7, 20, dragonflies, has shown effectiveness in solving various 23]. However, many of these methods face limitations optimization problems [19, 29, 30, 31, 32, 36]. when dealing with the complex dynamics and This article proposes and analyzes a hypothetical uncertainties of CDPRs. For instance, linear controllers Optimized Adaptive Fuzzy Synergetic Controller may not perform well across the entire workspace due (OAFSC) for suspended CDPRs. The OAFSC leverages to varying dynamics, while purely model-based the strengths of AFSC for robust adaptive control and nonlinear controllers require accurate system utilizes the Dragonfly Algorithm to optimize the parameters, which are often difficult to obtain in controller's parameters for enhanced trajectory practice [23]. tracking performance and robustness while considering Fuzzy Logic Control (FLC) has emerged as a powerful the positive cable tension constraint. tool for handling systems with uncertainties and METHODS nonlinearities without requiring a precise This section outlines the hypothetical methodology for mathematical model [6, 7, 28]. FLC utilizes linguistic designing, optimizing, and evaluating the proposed rules and fuzzy sets to map input variables (e.g., Optimized Adaptive Fuzzy Synergetic Controller tracking error, rate of error change) to control outputs. (OAFSC) for a suspended Cable-Driven Parallel Robot Adaptive fuzzy control further enhances robustness by (CDPR). adjustin