Studies on PI/PID controllers in the proportional integral plane via different performance indices

2016 ◽  
Author(s):  
Saurabh Srivastava ◽  
V. S. Pandit
Keyword(s):  
Pid Controllers ◽  
Performance Indices ◽  
Proportional Integral ◽  
Integral Plane

scholarly journals Position Tracking of ML System using CSA Based PID Controller

2019 ◽  
Vol 8 (11) ◽  
pp. 1956-1959
Keyword(s):  
Pid Controller ◽  
Magnetic Levitation ◽  
Search Algorithm ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Pid Controllers ◽  
Position Tracking ◽  
Proportional Integral Derivative ◽  
Proportional Integral ◽  
Simulation Results

The classical proportional integral derivative (PID) controllers are still use in various applications in industry. Magnetic levitation (ML) systems are rigidly nonlinear and sometimes unstable systems. Due to inbuilt nonlinearities of ML systems, tracking of position of ML Systems is still difficult. For the tracking purpose of position, PID controller parameters are found by choosing Cuckoo Search Algorithm (CSA) of optimization. The ranges of parameters are customized by z-n method of parameters. Simulation results show the tracking of position of ML systems using conventional and optimized parameters obtained with the CSA based controller.

The Parameterization of All Plants Stabilized by Proportional Controller Formultiple-Input/Multiple-Output Plant

2011 ◽  
Vol 497 ◽  
pp. 246-254
Author(s):  
Takaaki Hagiwara ◽  
Kou Yamada ◽  
Satoshi Aoyama ◽  
An Chinh Hoang
Keyword(s):  
Pid Controller ◽  
Multiple Input Multiple Output ◽  
Pid Controllers ◽  
Proportional Integral Derivative ◽  
Proportional Integral ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Proportional Controller

In this paper, we examine the parameterization of all plants stabilized by a proportionalcontroller for multiple-input/multiple-output plant. A proportional controller is a kind of Proportional-Integral-Derivative (PID) controllers. PID controller structure is the most widely used one in industrialapplications. Recently, if stabilizing PID controllers for the plant exist, the parameterization of allstabilizing PID controllers has been considered. However, no paper examines the parameterizationof all plants stabilized by a PID controller. In this paper, we clarify the parameterization of all plantsstabilized by a proportional controller for multiple-input/multiple-output plant. In addition, we presentthe parameterization of all stabilizing proportional controllers for the plant stabilized by a proportionalcontroller.

New Analysis/Design of Generalized Discrete PI Controller via Discrete Time Delay Control for Nonlinear Systems

2020 ◽  
Author(s):  
Suresh B. Reddy
Keyword(s):  
Time Delay ◽  
Nonlinear Systems ◽  
Discrete Time ◽  
Linear Time ◽  
Sufficient Conditions ◽  
Pi Controller ◽  
Pid Controllers ◽  
Analysis And Design ◽  
Proportional Integral ◽  
Discrete Time Delay

Abstract Proportional-Integral (PI) and Proportional-Integral-Derivative (PID) controllers are among the most common schemes for control since their formulation nearly a century ago. They have been very successful in many applications, even as we have migrated from analog implementations to digital control systems. While there is rich literature for design and analysis of PI/PID controllers for linear time-invariant systems with modeled dynamics, the tools for analysis and design for nonlinear systems with unknown dynamics are limited, despite their known effectiveness. This paper extends previous observations about a form of discrete Time Delay Control’s equivalence to a generalized PI controller for more general canonical systems, with additional complimentary feedback linearization of known dynamics, as desired. In addition, sufficient conditions for Bounded Input-Bounded Output (BIBO) as well as exponential stability are developed in this paper for the form of discrete TDC that is closest to generalized discrete PI equivalent controller, for multi-input multi-output nonlinear systems, including nonaffine cases. Accordingly, design procedures are suggested for such discrete TDC, and generalized discrete PI controller for nonlinear systems.

The Parameterization of All Plants Stabilizied by a PID Controller for Multiple-Input/Multiple-Output Plants

2013 ◽  
Vol 596 ◽  
pp. 158-167
Author(s):  
Takaaki Hagiwara ◽  
Kou Yamada ◽  
An Chinh Hoang ◽  
Satoshi Aoyama ◽  
Huo Hui
Keyword(s):  
Pid Controller ◽  
Multiple Input Multiple Output ◽  
Pid Controllers ◽  
Proportional Integral Derivative ◽  
Proportional Integral ◽  
Multiple Input ◽  
Input Multiple Output

In this paper, we examine the parameterization of all plants that can be stabilized bya Proportional–Integral–Derivative (PID) controller for multiple-input/multiple-output plants.The PID controller structure is the most widely used controller structure in industrial appli-cations. Recently, if stabilizing PID controllers for the plant exist, the parameterization of allstabilizing PID controllers was considered. However, the parameterization of all plants that canbe stabilized by a PID controller for multiple-input/multiple-output plants has not been exam-ined. In this paper, we clarify this question. In addition, we present the parameterization of allstabilizing PID controllers for multiple-input/multiple-output plants that can be stabilized bya PID controller.

Networked Control of a Large Pressurized Heavy Water Reactor (PHWR) With Discrete Proportional-Integral-Derivative (PID) Controllers

2013 ◽  
Vol 60 (5) ◽  
pp. 3879-3888 ◽  
Author(s):  
Soumya Dasgupta ◽  
Avijit Routh ◽  
Shohan Banerjee ◽  
K. Agilageswari ◽  
R. Balasubramanian ◽  
...  
Keyword(s):  
Heavy Water ◽  
Networked Control ◽  
Pid Controllers ◽  
Proportional Integral Derivative ◽  
Water Reactor ◽  
Proportional Integral ◽  
Heavy Water Reactor

scholarly journals Ziegler-Nichols Based Proportional-Integral-Derivative Controller for a Line Tracking Robot

2018 ◽  
Vol 9 (1) ◽  
pp. 221 ◽  
Author(s):  
Kim Seng Chia
Keyword(s):  
Pid Controller ◽  
Control Strategies ◽  
Tracking Task ◽  
Pid Controllers ◽  
Proportional Integral Derivative ◽  
Proportional Integral ◽  
Pid Algorithm ◽  
Tracking Process ◽  
Line Tracking ◽  
Proportional Controller

<p>Line tracking robots have been widely implemented in various applications. Among various control strategies, a proportional-integral-derivative (PID) algorithm has been widely proposed to optimize the performance of a line tracking robot. However, the motivation of using a PID controller, instead of a proportional (P) or a proportional-integral (PI) controller, in a line tracking task has seldom been discussed. Particularly, the use of a systematic tuning approach e.g. closed loop Ziegler Nichols rule to optimize the parameters of a PID controller has rarely been investigated. Thus, this paper investigates the performance of P, PI, and PID controllers in a line tracking task, and the ability of Ziegler Nichols rule to optimize the parameters of the P, PI, and PID controllers. First, the ultimate gain value, K<sub>u</sub> and ultimate period of oscillation, P<sub>u</sub> were estimated using a proposed approach. Second, the values of K<sub>P</sub>, K<sub>I</sub> and K<sub>D</sub> were estimated using the Ziegler Nichols formulae. The performance of a differential wheeled robot in the line tracking task was evaluated using three different speeds. Results indicate that the Ziegler Nichols rule coupled with the proposed method is able to identify the parameters of the P, PI, and PID controllers systematically in the line tracking task. Findings indicate that the mobile robot coupled with a proportional controller achieved the best performance compared to PI and PID controllers in the line tracking process when the estimated initial parameters were used.</p>

scholarly journals Back to Basics: Meaning of the Parameters of Fractional Order PID Controllers

Mathematics ◽  
2019 ◽  
Vol 7 (6) ◽  
pp. 530 ◽  
Author(s):  
Inés Tejado ◽  
Blas Vinagre ◽  
José Traver ◽  
Javier Prieto-Arranz ◽  
Cristina Nuevo-Gallardo
Keyword(s):  
Fractional Order ◽  
Pid Controllers ◽  
Integral Term ◽  
Error Curve ◽  
Proportional Integral ◽  
Pid Algorithm ◽  
Prediction Horizon ◽  
Noise Filter ◽  
Time Required ◽  
Fractional Order Pid

The beauty of the proportional-integral-derivative (PID) algorithm for feedback control is its simplicity and efficiency. Those are the main reasons why PID controller is the most common form of feedback. PID combines the three natural ways of taking into account the error: the actual (proportional), the accumulated (integral), and the predicted (derivative) values; the three gains depend on the magnitude of the error, the time required to eliminate the accumulated error, and the prediction horizon of the error. This paper explores the new meaning of integral and derivative actions, and gains, derived by the consideration of non-integer integration and differentiation orders, i.e., for fractional order PID controllers. The integral term responds with selective memory to the error because of its non-integer order λ , and corresponds to the area of the projection of the error curve onto a plane (it is not the classical area under the error curve). Moreover, for a fractional proportional-integral (PI) controller scheme with automatic reset, both the velocity and the shape of reset can be modified with λ . For its part, the derivative action refers to the predicted future values of the error, but based on different prediction horizons (actually, linear and non-linear extrapolations) depending on the value of the differentiation order, μ . Likewise, in case of a proportional-derivative (PD) structure with a noise filter, the value of μ allows different filtering effects on the error signal to be attained. Similarities and differences between classical and fractional PIDs, as well as illustrative control examples, are given for a best understanding of new possibilities of control with the latter. Examples are given for illustration purposes.

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