The regulator needs to control the plant to ensure its operation.ĭesign specifications can be chosen with countless combinations, and many specifications are contradictory. When designing a control system, the purpose of the closed-loop system is to comply with the response to a given input with a set of specifications, both with regard to the transient stage and to the steady state stage corresponding to the response. The current versions of Matlab also have Simulink blocks that behave as PID regulators with various structures, continuous or discrete, and with several variants of discretization in the latter case. Most programmable logic controllers (PLCs) have functions for implementing PID controllers.
In industrial practice, which includes both processes and electrical drives, more than 95% of the regulators used in the existing control loops are PIDs 2. It can also use any transfer function, physically feasible, implemented in a discrete (or continuous), state-space control, adaptive control strategy, or employ artificial intelligence techniques. The regulator can be of PID type or use any other structure, (e.g. Finally, section six present the conclusions and recommendations for continuing this type of research. The fifth section compares the proposed method with the poles location method. A third section describes the plant that will be used as an example for the application of the proposed method, which is detailed with the exposition and demonstration of the analytical relations used in the fourth section. The paper is presented in the following form: after this introduction, a second section briefly discusses the design of regulators. Based on previously established values of behavioral indexes and based on previously established models, this paper calculates the PID regulator parameters in general, and the proportional-integral (PI) type in particular. This is the goal of the research reported in this paper. It is necessary, however, to continue investigating alternative methods to improve the accuracy of calculating the regulator parameters and to achieve a more precise connection between the indices of desired behavior and those that are actually obtained. the closed-loop dynamic behavior indexes). They usually provide an acceptable fulfillment of the objectives in relation to the design specifications (i.e. This is the case of methods based on frequency response, where characteristics such as bandwidth and phase margin are specified which are related to the speed of response and the oscillatority.Īll of these methods, with their comparative advantages and disadvantages, have been well studied. Other methods indirectly seek the transient performance from various parameters. Several methods work on specifications in response to input signals, as in the optimal and symmetric module. There are also methods based on optimization that seek to minimize a function of tracking error and multiple variants 4.Ī common goal pursued by all these methods to obtain a control system with stable operation in a closed loop. In the latter case, the direct design method, also known as the Ragazzini method 3, is found. On the other hand, the analytical methods use a known mathematical model of the plant to reach the controller through mathematical operations. They do not need to know the model of the plant, but only some characteristics of its response to predict signals. On the one hand, we find the experimental method, among which is the widely used Ziegler-Nichols method 1 and its variants as proposed by Chien, Hrons and Reswick 2. There are many different methods of designing proportional-integral-derivative (PID) controllers.