Control of Pneumatic Artificial Muscles Using Local Cyclic Inputs and Genetic Algorithm
نویسندگان
چکیده
منابع مشابه
Robust Control Law for Pneumatic Artificial Muscles
This paper presents a modified integral sliding surface, sliding mode control law for pneumatic artificial muscles. The cutoff frequency tuning parameter λ is squared to increase the gradient from absement (integral of position) to position and higher derivatives to reflect the more dominant terms in the actuator dynamics. The sliding mode controller is coupled with proportional and integral ac...
متن کاملPneumatic Artificial Muscles
This paper reports mechanical tasting and modeling results for the McKibben artificial muscle pneumatic actuator. This device, first developed in the 1950’s, contains an expanding tube surrounded by braided cords. We report static and dynamic length-tension testing results and derive a linearized model of these properties for three different models. The results are brieffy compared with human m...
متن کاملControl architecture of LUCY, a Biped with Pneumatic Artificial Muscles
This paper describes the biped Lucy and it’s control architecture that will be used. Lucy is actuated by Pleated Pneumatic Artificial Muscles, which have a very high power to weight ratio and an inherent adaptable compliance. These characteristics will be used to let Lucy walk in a dynamically stable manner while exploiting the adaptable passive behaviour of these muscles. A quasi-static global...
متن کاملStatic Force Model of Pneumatic Artificial Muscles
Pneumatic actuators convert pneumatic energy into mechanical motion. This motion can be linear or rotary. Linear motion is feasible with pneumatic cylinders (e. g. single-acting cylinder, double-acting cylinder, rodless cylinder) and pneumatic artificial muscles (PAMs). Pneumatic artificial muscle is the newest and most promising type of pneumatic actuators. PAM is a membrane that expands radia...
متن کاملA Hybrid Algorithm using Firefly, Genetic, and Local Search Algorithms
In this paper, a hybrid multi-objective algorithm consisting of features of genetic and firefly algorithms is presented. The algorithm starts with a set of fireflies (particles) that are randomly distributed in the solution space; these particles converge to the optimal solution of the problem during the evolutionary stages. Then, a local search plan is presented and implemented for searching s...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Actuators
سال: 2018
ISSN: 2076-0825
DOI: 10.3390/act7030036