Linear and nonlinear arx model for intelligent pneumatic actuator systems

System modeling in describing the dynamic behavior of the system is very important and can be considered as a challenging problem in control systems engineering. This article presents the linear and nonlinear approaches using AutoRegressive with Exogenous Input (ARX) model structure for the modeling of position control of an Intelligent Pneumatic Actuator (IPA) system. The input and output data of the system were obtained from real-time experiment conducted while the linear and nonlinear mathematical models of the system were obtained using system identification (SI) technique. Best fit and Akaike’s criteria were used to validate the models. The results based on simulation reveals that nonlinear ARX (NARX) had the best performance for the modeling of position control of IPA system. The results show that nonlinear modeling is an effective way of analyzing and describing the dynamic behavior and characteristics of IPA system. This approach is also expected to be able to be applied to other systems. A future study exploring the execution of other model structures in demonstrating the position control of IPA system would be exceptionally intriguing

Enhanced Position Control for Pneumatic System by Applying Constraints in MPC Algorithm

This paper demonstrates the effectiveness of applying constraints in a controller algorithm as a strategy to enhance the pneumatic actuator system’s positioning performance. The aim of the present study is to reduce the overshoot in the pneumatic actuator positioning system’s response. An autoregressive with exogenous input (ARX) model structure has been used to model the pneumatic system, while a model predictive control (MPC) has been employed as a control strategy. The input constraint has been applied to the control signals (on/off valves signals) to ensure accurate position tracking. Results show that the strategy with constraint effectively reduced overshoot by more than 99.0837 % and 97.0596 % in simulation and real-time experiments, respectively. Moreover, the performance of the proposed strategy in controlling the pneumatic positioning system is considered good enough under various loads. The proposed strategy can be applied in any industry that used pneumatic actuator in their applications, especially in industries that involved with position control such as in manufacturing, automation and robotics. The strategy proved to be capable of controlling the pneumatic system better, especially in the real-time environment

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

Design and Development of Ankle-Foot Rehabilitation Exerciser (AFRE) System Using Pneumatic Actuator

This research presents the design and development of a novel strategy for an Ankle-Foot Rehabilitation Exerciser (AFRE) system. AFRE system can be used Continuous Passive Motion (CPM) device and strength endurance training device for early stage functional rehabilitation. The designed mechanism can allow desired maximum and minimum Range of Motion (ROM) for dorsiflexion and plantar flexion (upwards and downwards stretching). This device consists of a new moveable mechanism design prototype using a new double acting Intelligent Pneumatic Actuator (IPA), embedded controller and communication protocol. The drive system consists of a nonlinear moving pneumatic actuator that controls the angle position, force and compliance for stiffness characteristic of the ankle-foot orthosis platform. In addition, the device can be configured through MATLAB via personal computer where the user can adjust the required ROM and resistance for the user in real-time. Analysis carried out during the system validation and testing through selected subjects are presented and discussed. This AFRE system is expected to substitute the traditional therapy and motorized rehabilitation device to increase the healing time of the patient specifically

Identification And Non-Linear Control Strategy For Industrial Pneumatic Actuator

In this paper, a combination of nonlinear gain and proportional integral derivative (NPID) controller was proposed to the trajectory tracking of a pneumatic positioning system. The nonlinear gain was employed to this technique in order to avoid overshoot when a relatively large gain is used to produce a fast response. This nonlinear gain can vary automatically either by increasing or decreasing depending on the error generated at each instant. Mathematical model of a pneumatic actuator plant was obtained by using system identification based on input and output of open-loop experimental data. An auto-regressive moving average with exogenous (ARMAX) model was used as a model structure of the system. The results of simulation and experimental tests conducted for pneumatic system with different kind of input namely step, sinusoidal, trapezoidal and random waveforms were applied to evaluate the performance of the proposed technique. The results reveal that the proposed controller is better than conventional PID controller in terms of robust performance as well as show an improvement in its accuracy

Modeling and fuzzy FOPID controller tuned by PSO for pneumatic positioning system

A pneumatic cylinder system is believed to be extremely nonlinear and sensitive to nonlinearities, which makes it challenging to establish precise position control of the actuator. The current research is aimed at reducing the overshoot in the response of a double-acting pneumatic actuator, namely, the IPA positioning system’s reaction time. The pneumatic system was modeled using an autoregressive with exogenous input (ARX) model structure, and the control strategy was implemented using a fuzzy fractional order proportional integral derivative (fuzzy FOPID) employing the particle swarm optimization (PSO) algorithm. This approach was used to determine the optimal controller parameters. A comparison study has been conducted to prove the advantages of utilizing a PSO fuzzy FOPID controller over PSO fuzzy PID. The controller tuning algorithm was validated and tested using a pneumatic actuator system in both simulation and real environments. From the standpoint of time-domain performance metrics, such as rising time (tr), settling time (ts), and overshoot (OS%), the PSO fuzzy FOPID controller outperforms the PSO Fuzzy PID controller in terms of dynamic performance