Intelligent self-tuning of PID control for the robotic testing system for human musculoskeletal joints test.
In this paper, an intelligent proportional-integral-derivative (PID) control method is introduced to the robotic testing system for the biomechanical study of human musculoskeletal joints. For the testing system, the robot is a highly nonlinear and heavily coupled complicated system, and the human spinal specimen also demonstrates nonlinear property when undergoing testing. Although the conventional PID control approach is extensively used in most industrial control systems, it will break down for nonlinear systems, particularly for complicated systems that have no precise mathematical models. To overcome those difficulties, an intelligent fuzzy PID controller is proposed replacing the widely used conventional PID controllers. The fuzzy PID algorithm is outlined using the fuzzy set theory. The design techniques are developed based on the linguistic phase plane approach. The heuristic rules of syntheses are summarized into a rule-based expert system. Experiments are carried out and the results demonstrate the good performance of the robotic testing system using the proposed control method.
Tian
Lianfang
L
Department of Orthopaedic Surgery, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA. chlftian@hotmail.com
D000465:Algorithms; D001185:Artificial Intelligence; D001842:Bone and Bones / Q000502:physiology*; D004548:Elasticity; D004867:Equipment Design; D019544:Equipment Failure Analysis; D005246:Feedback; D017143:Fuzzy Logic; D006801:Humans; D007596:Joints / Q000502:physiology*; D018482:Muscle, Skeletal / Q000502:physiology*; D010808:Physical Examination / Q000295:instrumentation* / Q000379:methods; D010812:Physical Stimulation / Q000295:instrumentation* / Q000379:methods; D012371:Robotics / Q000295:instrumentation* / Q000379:methods; D013314:Stress, Mechanical