Prediction of peak ground acceleration of Iran's tectonic regions using a hybrid soft computing technique

A new model is derived to predict the peak ground acceleration (PGA) utilizing a hybrid method coupling artificial neural network (ANN) and simulated annealing (SA), called SA-ANN. The proposed model relates PGA to earthquake source to site distance, earthquake magnitude, average shear-wave velocity, faulting mechanisms, and focal depth. A database of strong ground-motion recordings of 36 earthquakes, which happened in Iran's tectonic regions, is used to establish the model. For more validity verification, the SA-ANN model is employed to predict the PGA of a part of the database beyond the training data domain. The proposed SA-ANN model is compared with the simple ANN in addition to 10 well-known models proposed in the literature. The proposed model performance is superior to the single ANN and other existing attenuation models. The SA-ANN model is highly correlated to the actual records (R = 0.835 and ρ = 0.0908) and it is subsequently converted into a tractable design equation

Implementation of PID, bang-bang and backstep-ping controllers on 3D printed ambidextrous robot hand

Robot hands have attracted increasing research interest in recent years due to their high demand in industry and wide scope in number of applications. Almost all researches done on the robot hands were aimed at improving mechanical design, clever grasping at different angles, lifting and sensing of different objects. In this chapter, we presented the detail classification of control systems and reviewed the related work that has been done in the past. In particular, our focus was on control algorithms implemented on pneumatic systems using PID controller, Bang-bang controller and Backstepping controller. These controllers were tested on our uniquely designed ambidextrous robotic hand structure and results were compared to find the best controller to drive such devices. The five finger ambidextrous robot hand offers total of 13 degrees of freedom (DOFs) and it can bend its fingers in both ways left and right offering full ambidextrous functionality by using only 18 pneumatic artificial muscles (PAMs).Anthony Huynh, Luke Steele, Michal Simko, Luke Kavanagh and Alisdair Nimm