Digital control for human arm based multi objective Particle Swarm Optimization

Soft computing research is concerned with the integration of artificial intelligent tools in a complementary hybrid framework for solving real world problems. This work presents a simulation of artificial human arm. The work includes mathematical modeling of the kinematics and the dynamics of the human arm. The model permits direct forward dynamics simulation, which accurately predicts arm position, also presents a solution to the inverse problem of determining set of joints angle to achieve a given position or motion. This paper tries to explore the potential of using soft computing methodologies in control of plant (human arm). It presents a PD tuning method that uses a Particle Swarm Optimization (PSO) as a main gain of PD tuning using multi objective to improve the time response of system such settling time and overshoot. This paper presents a strategy based on combine´s analytical solutions with nonlinear optimization algorithm solutions to solution the IKP. A analytical solutions is used to reduce the size of problem from seven variable of joint angle to single variable and nonlinear optimization algorithm was used to find approximate solution which make the computation time is very small.