Basically, the intelligent pneumatic actuator is equipped with two sensors of optical encoder and pressure sensor. A miniature valve is attached at the end of the cylinder and a microcontroller board consists of Programmable System on a Chip (PSoC) as the central processing unit is fixed at the top of the actuator, in a single device. The intelligence aspect of this actuator is that it can decide the output target based on the feedback inputs with real-time communication capability. The actuator has 200mm stroke and can give force up to 100N. The 0.169mm laser stripe pitch can give high accuracy for position control. An optical reflective surface mount encoder chip is implemented on the bottom part of the PSoC circuit board. This encoder chip consists of three parts; an LED light source, a photo detector IC and optical lenses. The lenses focus LED light onto the code strips on the guide rod and reflected light on the photo detector IC. Fig. 1 shows overall parts of the intelligent actuator.
Project 1 by :
MODELING, POSITION AND VISCOSITY CONTROL OF INTELLIGENT PNEUMATIC ACTUATOR
Intelligent pneumatic actuator (IPA) is a new developed actuator which integrates actuator, and others new features such as microcontroller and various micro sensors. This type of actuator has the capability to communicate with computer to give better control, higher position and force accuracy. In prior to that, several experimental setup for the stiffness and viscosity control had been done using conventional PI controller. The previous experimental results showed that these control algorithms were feasible for the real IPA system. In this project, the work focuses more on the reverse engineering method, which is from existing real IPA system which had been developed by Dr. Ahmad ‘Athif Mohd Faudzi, to simulation analysis for the validation of other controllers.
The objectives of this project are to develop a simulation model to represent the real IPA system, and design other controllers to be applied in this developed simulation model. For the simulation model, nonlinear mathematical modeling based on fundamental physical derivation is presented. Open-loop and closed-loop simulation works are done to confirm this model based on this derivation. Closed-loop IPA system is divided into two main control algorithms, which are position control for position tracking control and viscosity control for force tracking control. Several controllers which are related to the fuzzy logic are designed and applied to these control algorithms. The simulation results from these controllers are then validated and compared with result of using conventional PI controller. The comparison is made by analyzing their performances based on control theory. Lastly, due to the nonlinearities problem exist in nonlinear mathematical model, linearization method is proposed to obtain a new linear model to ease the controller design and analysis. For the future research, it is recommended to implement all the proposed controllers to the real-time IPA system.
Project 2 by :
SYSTEM IDENTIFICATION AND PI NEURO-FUZZY CONTROL OF A PNEUMATIC ACTUATOR
Pneumatic actuators have a number of advantages over electric motors, including strength-to-weight ratio, tunable compliance at the mechanism level, robustness, as well as the low price. The Intelligent Pneumatic Actuators (IPA) is a new generation of actuators for research and development (R&D). This research proposes a force model of IPA based on system identification technique. A proportional derivative adaptive neuro fuzzy controller (PI-ANFIS) is presented to validate the new model with real time results. The position IPA is controlled by P-ANFIS controller in MATLAB simulation environment and applied on the real IPA plant. Thereafter the stiffness characteristic of IPA is tested in simulation environment by using two different control techniques based on the proposed position and force control. Finally, a comparison is made between the obtained results and showed that, the objectives were achieved successfully.