Abstract
This paper presents the real-time implementation of a fuzzy coordinated classical PI control scheme for controlling the pressure in a pilot pressure tank system. The fuzzy system has been designed to track the variation parameters in a feedback loop and tune the classical controller to achieve a better control action for load disturbances and set point changes. The error and process inputs are chosen as the inputs of fuzzy system to tune the conventional PI controller according to the process condition. This online conventional controller tuning technique will reduce the human involvement in controller tuning and increase the operating range of the conventional controller. The proposed control algorithm is experimentally implemented for the real-time pressure control of a pilot air tank system and validated using a high-speed 32-bit ARM7 embedded microcontroller board (ATMEL AT91M55800A). To demonstrate the performance of the fuzzy coordinated PI control scheme, results are compared with a classical PI and PI-type fuzzy control method. It is observed that the proposed controller structure is able to quickly track the parameter variation and perform better in load disturbances and also for set point changes.
Highlights
The classical controllers like PI or PID controllers are widely used in process industries because of their simple structure, assure acceptable performance for industrial processes and their tuning is well known among all industrial operators
This paper reports the design and implementation of a fuzzyPI hybrid controller structure in which the fuzzy controller is adapted to track error and process input of a feedback system and tune the classical PI controller for set point changes and load disturbances
In the present application, a modified control structure has been applied in which the fuzzy system utilize the error (e) and process input (u) and detects the possible deviation from a prescribed course so that it can able to tune the conventional controller for set point changes and load disturbances
Summary
The classical controllers like PI or PID controllers are widely used in process industries because of their simple structure, assure acceptable performance for industrial processes and their tuning is well known among all industrial operators. In the present industrial scenario, all the processes require automatic control with good performance over a wide operating range with simple design and implementation. This provides the motivation for online tuning, where the focus is on the automatic online synthesis and tuning of the conventional controller parameters, that is, using the online data, the adopted intelligent system can continually learn which will ensure that the performance objectives are met. A fuzzy inference system is used to tune the PI controller gains depending on the current operating conditions of the controlled system
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