62 research outputs found
Integrating Servo-Pneumatic Actuator with Ball Beam System based on Intelligent Position Control
The purpose of this paper is to design a controller that can control the position of the cylinder pneumatic stroke. This work proposes two control approaches, Proportional-Integral-Derivative Fuzzy Logic (Fuzzy-PID) controller and Proportional-Derivative Fuzzy Logic (PD-Fuzzy) controller for a Servo-Pneumatic Actuator. The design steps of each controller implemented on MATLAB/Simulink are presented. A model based on position system identification is used for the controller design. Then, the simulation results are analyzed and compared to illustrate the performance of the proposed controllers. Finally, the controllers are tested with the real plant in real-time experiment to validate the results obtained by simulation. Results show that PD-Fuzzy controller offer better control compared to Fuzzy-PID. A Pneumatic Actuated Ball & Beam System (PABBS) is proposed as the application of the position controller. The mathematical model of the system is developed and tested simulation using Feedback controller (outer loop)-PD-Fuzzy controller (inner loop). Simulation result is presented to see the effectiveness of the obtained model and controller. Results show that the servo-pneumatic actuator can control the position of the Ball & Beam system using PD-Fuzzy controller
A new technique to reduce overshoot in pneumatic positioning system
This paper presents a new approach for improving the performance of the pneumatic positioning system by incorporating a nonlinear gain function with observer system. System identification technique has been employed to represent the pneumatic system, while a model predictive control (MPC) with the observer system has been employed as the main controller to control the positioning of the system. The nonlinear gain function has been incorporated with the control strategy to compensate nonlinearities and uncertainties inherent in the parameters of the system. Unconstrained and constrained cases of control signals have been considered in this study. Simulation based on Matlab/Simulink indicated a reduction in overshoot of the system response for both cases due to additional nonlinear gain function in the strategy. Furthermore, remarkable enhancement was observed in effectiveness of this function while incorporated in constrained case, when this new strategy successfully improved the transient response in the pneumatic positioning system
Performance Analysis For Sprain Ankle Rehabilitation System Using Gyro Sensor
Sprain ankle rehabilitation is an exercise to recover full function without limitations and strength of ankle joint under the therapist exercise. Recently, ankle rehabilitation technique is enhanced using an intelligent system compared to a conventional technique. Patients mainly perform ankle exercise by manual therapy can cause a loose interest for them to continue the activity. The objectives of this study are to propose and develop an ankle rehabilitation system platform that acts as a user-friendly device able to execute an ankle with 3 Degrees of Freedom (DoF). The develop device consists of a microcontroller, servo motor, gyro sensor, Wi-Fi Module and Graphical User Interface. The microcontroller connected via internet connectivity with smartphones to control modes of exercise at different speeds according to the user's circumstances. A gyro sensor is embedded onto the robotic platform in order to measure the limitation position angle of the patient’s. The closer the tilt angle achieved reflects the recovery which near to the normal person. The strength movement of ankle ability given by each participant almost 55% able to achieve the limitation range angle for the lower torque stiffness power supply of the servo motor. For higher torque stiffness power supply, almost 35% of each participant’s able to reach the limitation range of movement. Based on the result obtained, the Ankle Rehabilitation System device manages to help significantly or almost fully improve the time healing of sprain ankle patients with more interesting motorized rehabilitation devices compared to a traditional device
Modified Predictive Control for a Class of Electro-Hydraulic Actuator
Many model predictive control (MPC) algorithms have been proposed in the literature depending on the conditionality of the system matrix and the tuning control parameters. A modified predictive control method is proposed in this paper. The modified predictive method is based on the control matrix formulation combined with optimized move suppression coefficient. Poor dynamics and high nonlinearities are parts of the difficulties in the control of the Electro-Hydraulic Actuator (EHA) functions, which make the proposed matrix an attractive solution. The developed controller is designed based on simulation model of a position control EHA to reduce the overshoot of the system and to achieve better and smoother tracking. The performance of the designed controller achieved quick response and accurate behavior of the tracking compared to the previous study
Development of Nonlinear Adaptive PI Controller For Improved Pneumatic Actuator System
The wide application of pneumatic actuator in electrical and electronics sectors are undeniable hence ask for a good control environment. PID controller is always known with easy implementation and good control performance. But the limitation of the PID static gains to effectively control the complex nonlinear system is unavoidable. This suggests the enhancement of the PI controller with a nonlinear adaptive interaction algorithm (AIA). The modification is introduced by integrating a nonlinear gain function that adaptively tunes the AIA parameter, hence resulting the best tuning of the PI control gains. The uncertainties and nonlinearities inherent in the system parameters are believed to be handled by the integration, therefore improving the controller performances while maintaining the pneumatic actuator at the desired position. It was proved that improved error performance criteria’s, settling time and overshoot were resulted by the nonlinear AIA PI compared to fix AIA PI. Besides, the nonlinear AIA PI has successfully reduced the overshoot to 5.35% and 6.70% compared to optimal AIA PI and optimal PI controller, respectively. To conclude, the development of the proposed controller is demonstrated to function well and offers an alternative tuning strategy in other electronical and electronic engineering applications
Development of Nonlinear Adaptive PI Controller For Improved Pneumatic Actuator System
The wide application of pneumatic actuator in electrical and electronics sectors are undeniable hence ask for a good control environment. PID controller is always known with easy implementation and good control performance. But the limitation of the PID static gains to effectively control the complex nonlinear system is unavoidable. This suggests the enhancement of the PI controller with a nonlinear adaptive interaction algorithm (AIA). The modification is introduced by integrating a nonlinear gain function that adaptively tunes the AIA parameter, hence resulting the best tuning of the PI control gains. The uncertainties and nonlinearities inherent in the system parameters are believed to be handled by the integration, therefore improving the controller performances while maintaining the pneumatic actuator at the desired position. It was proved that improved error performance criteria’s, settling time and overshoot were resulted by the nonlinear AIA PI compared to fix AIA PI. Besides, the nonlinear AIA PI has successfully reduced the overshoot to 5.35% and 6.70% compared to optimal AIA PI and optimal PI controller, respectively. To conclude, the development of the proposed controller is demonstrated to function well and offers an alternative tuning strategy in other electronical and electronic engineering applications
Predictive Functional Controller (PFC) with Novel Observer Method for Pneumatic Positioning System
Nowadays, the pneumatic system is more complex which leads to the development of an intelligent pneumatic system. Due to the difficulties in controlling the position and force of pneumatic actuators nonlinearities existed. This paper proposes a design of Predictive Functional Control (PFC) using two different types of observers such as full-order and reduced order as a novel method to come out with these issues. The mathematical model of the pneumatic system come from System Identification (SI) method and third order Auto-Regressive with Exogenous Input (ARX) has been chosen as a model structure. Matlab/Simulink has been utilized as the platform and the performance of the controller using both observers have been validated in simulation and real-time experiment. The comparison has been made to identify which observers are more efficient by taking into account the value of Steady State Error (Sse), Percentage of Overshoot (%Os), Settling Time (Ts) and Rise Time (Tr). Real-time experiment results show that the strategy using reduced-order observer is more efficient because this strategy can reduce more Sse
Production of Agarwood Resin in Aquilaria beccariana Using Inducement Technology
Agarwood is a type of resin impregnated wood produced from the wounded Aquilaria trees. This agarwood gives a pleasant fragrant when it is burned. It becomes high-priced and increase demanded in the world due to the depletion of wild agarwood in the forest caused by illegal poaching activities. Agarwood resin can only be produced by injuring caused by lightning or wounded by animals under natural conditions. However, the natural process of resin accumulation is uncertain and time-consuming. Therefore, we developed an agarwood inducement technique that served as the alternative way to induce the agarwood formation in a short time. Three inducement techniques, including the injecting method, knocking method and combination of injecting & knocking method were applied to induce resin formation. In this study, we evaluated the technique for producing agarwood in species Aquilaria beccariana, which is native and only can be found in Borneo Malaysia. For A. beccariana trees treated with the inducement technique, resin formed and spread throughout the cell in the trunk. The evaluation results showed that the agarwood yield per tree reached around 5 to 7 kilogram. Furthermore, this agarwood derived from the induction was found to have a similar quality with the wild agarwood. This indicates the inducement technology had successfully produced agarwood resin in A. beccariana with a grade similar to the wild agarwood
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