Modeling and control of 5 DOF robot arm using supervisory control

Alassar, Ahmed Z.; Abuhadrous, Iyad M.; Elaydi, Hatem

doi:10.1109/iccae.2010.5451398

Cited by 18 publications

(20 citation statements)

References 36 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The velocity of each particle, adjusted according to its own flying experience and the other particle's flying experience. For example, the i th particle is represented as (3) in the d-dimensional space. The best previous position of the i th particle is recorded and represented as:…”

Section: Partical Swarm Optimization (Pso)mentioning

confidence: 99%

“…Therefore it is necessary to control the path which enables the tool of the robot to follow with high accuracy to avoid robot or tool destruction. In most control systems such as robots, PD controller considered the most and popular control Algorithm, because of its simple structure, ease of design and the robustness in operating condition [3].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Digital control for human arm based multi objective Particle Swarm Optimization

Al-Faiz

Ali

Hussien

2012

2012 First National Conference for Engineering Sciences (FNCES 2012)

View full text Add to dashboard Cite

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.

show abstract

Section: Partical Swarm Optimization (Pso)mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Digital control for human arm based multi objective Particle Swarm Optimization

Al-Faiz

Ali

Hussien

2012

2012 First National Conference for Engineering Sciences (FNCES 2012)

View full text Add to dashboard Cite

show abstract

“…A five degrees of freedom robot (5 DOFs) is equipped by a strain-gauge sensor with ball caster tip, which is in contact with materials to be identified [5], [6]. Robot is controlled by inverse kinematic approach and a PD controller.…”

Section: Introductionmentioning

confidence: 99%

“…1. Young's modulus correlates the stress which is produced due to the traction vector on a surface with strain of material which is also the consequent of applying force on surface of material (6). E   (6) Equation (6) shows that there is a linear relationship between the applied stress on surface of material and strain which is occurred because of change in length of material.…”

Section: Introductionmentioning

confidence: 99%