Modeling of McKibben Pneumatic artificial muscles using optimized Echo State Networks

In conventional techniques for modeling Pneumatic artificial muscle, there are difficulties such as poor knowledge of the process, inaccurate process or complexity of the resulting mathematical model. Trying to solve these problems, this study investigates the method of establishing the model using a novel network-Echo State Network (ESN). We introduce the mechanism of this net and apply it to our modeling work. The relevant parameters of the net were optimized using Particle Swarm Optimization (PSO). Then we get the simulation results which reveal that it can get quite satisfactory results.