Implementation of Iterative Learning Control on a Pneumatic Actuator.

Masters Degree. University of KwaZulu-Natal, Durban.Pneumatic systems play a pivotal role in many industrial applications, such as in petrochemical industries, steel manufacturing, car manufacturing and food industries. Besides industrial applications, pneumatic systems have also been used in many robotic systems. Nevertheless, a pneumatic system contains different nonlinear and uncertain behaviour due to gas compression, gas leakage, attenuation of the air in pipes and frictional forces in mechanical parts, which increase the system’s dynamic orders. Therefore, modelling a pneumatic system tends to be complicated and challenges the design of the controller for such a system. As a result, employing an effective control mechanism to precisely control a pneumatic system for achieving the required performance is essential. A desirable controller for a pneumatic system should be capable of learning the dynamics of the system and adjusting the control signal accordingly. In this study, a learning control scheme to overcome the highlighted nonlinearity problems is suggested. Many industrial processes are repetitive, and it is reasonable to make use of previously acquired data to improve a controller’s convergence and robustness. An Iterative Learning Control (ILC) algorithm uses information from previous repetitions to learn about the system’s dynamics. The ILC algorithm characteristics are beneficial in real-time control given its short time requirements for responding to input changes. Cylinder-piston actuators are the most common pneumatic systems, which translate the air pressure force into a linear mechanical motion. In industrial automation and robotics, linear pneumatic actuators have a wide range of applications, from load positioning to pneumatic muscles in robots. Therefore, the aim of this research is to study the performance of ILC techniques in position control of the rod in a pneumatic position-cylinder system. Based on theoretical analysis, the design of an ILC is discussed, showing that the controller can satisfactorily overcome nonlinearities and uncertainties in the system without needing any prior knowledge of the system’s model. The controller has been designed in such a way to even work on non-iterative processes. The performance of the ILC-controlled system is compared with a well-tuned PID controller, showing a faster and more accurate response

Implementation of Iterative Learning Control on a Pneumatic Actuator

Pneumatic actuators demonstrate various nonlinear and uncertain behavior, and as a result, precise control of such actuators with model-based control schemes is challenging. The Iterative Learning Control (ILC) algorithm is a model-free control method usually used for repetitive processes. The ILC uses information from previous repetitions to learn about a system’s dynamics for generating a more suitable control signal. In this paper, an ILC method to overcome the nonlinearities and uncertainties in a pneumatic cylinder-piston actuator is suggested. The actuator is modeled using MATLAB SimScape blocks, and the ILC scheme has been expanded for controlling nonlinear, non-repetitive systems so that it can be used to control the considered pneumatic system. The simulation results show that the designed ILC controller is capable of tracking a non-repetitive reference signal and can overcome the internal and payload uncertainties with the precision of 0.002 m. Therefore, the ILC can be considered as an approach for controlling the pneumatic actuators, which is challenging to obtain their mathematical modeling

Implementation of Iterative Learning Control on a Pneumatic Actuator

Pneumatic actuators demonstrate various nonlinear and uncertain behavior, and as a result, precise control of such actuators with model-based control schemes is challenging. The Iterative Learning Control (ILC) algorithm is a model-free control method usually used for repetitive processes. The ILC uses information from previous repetitions to learn about a system’s dynamics for generating a more suitable control signal. In this paper, an ILC method to overcome the nonlinearities and uncertainties in a pneumatic cylinder-piston actuator is suggested. The actuator is modeled using MATLAB SimScape blocks, and the ILC scheme has been expanded for controlling nonlinear, non-repetitive systems so that it can be used to control the considered pneumatic system. The simulation results show that the designed ILC controller is capable of tracking a non-repetitive reference signal and can overcome the internal and payload uncertainties with the precision of 0.002 m. Therefore, the ILC can be considered as an approach for controlling the pneumatic actuators, which is challenging to obtain their mathematical modeling