Unactuated Force Control of 5-DOF Parallel Robot Based on Fuzzy PI

Abstract

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Period-doubling bifurcation analysis and chaos control for load torque using FLC

“…Fuzzy logic controller (FLC) clarifies the experience and the knowledge of a human operator in linguistic variables (fuzzy rules) without any knowledge of parameter variations and dynamics of the system. Implementation of FLC depends upon the process done by human factors without the need for a mathematical model [41][42][43][44][45][46]. The fuzzy system consists of two inputs: the error and the change of error, and one output is the change of control output.…”

“…Besides, it improves performance and provides superior outcomes than other techniques. Hence, FLC gives better results with position control and DC/DC converters [42] and [44], stabilizes the induction motor [45], removes chaos in converters [41], and controls complicated, undefined chaotic systems Parameters [43,46].…”

Shearer Height Adjustment Based on Mechanical-Electrical-Hydraulic Cosimulation

“…In recent years, with the rapid development of computer technology, cosimulation technology has been widely used for solving multidomain problems [17], [18]. For instance, the cutting vibration behavior of the continuous miner [19], nonlinear motion behavior of the robot [20][21][22][23], complex fluid dynamics analysis and structural optimization design of variable displacement pump [24][25][26], fuel system design and fuel economy analysis of hybrid cars [27][28][29][30], and other mechanical-hydraulic cosimulations have been performed [31][32][33][34]. There are few literature reports focusing on cosimulation problems with three or more domains.…”

Neural Network-based Robust Anti-sway Control of an Industrial Crane Subjected to Hoisting Dynamics and Uncertain Hydrodynamic Forces

“…To address this issue, several effective control strategies have been developed for different structures and dynamics. These strategies can be categorized into open-loop control methods [1][2][3][4][5][6][7] and closed-loop control methods [8][9][10][11][12][13][14][15][16][17][18][19][20][21][22][23][24][25][26]. In particular, the well-developed open-loop control methods are input shaping-based approaches [1][2][3][4][5], which achieve simultaneous positioning control and swing elimination using linearized dynamics.…”

“…In contrast, feedback controllers have been developed to enhance the robustness of the control system while ensuring satisfactory performance in swing elimination. Several types of modern control meth- ods, such as delayed feedback control [8], adaptive nonlinear control [9][10][11][12], boundary control [13,14], sliding mode control [15][16][17][18][19][20][21][22][23], and intelligent control [24][25][26] are included in this category. Although the aforementioned methods for crane systems are effective, their direct application to the control problem of transporting underwater objects is inadvisable due to the complex sway motions, which are distinct from the dynamic behavior in air.…”