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>

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.

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 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.

scholarly journals Optimized Proportional-Integral-Derivative Controller for Upper Limb Rehabilitation Robot

Electronics ◽  
2019 ◽  
Vol 8 (8) ◽  
pp. 826 ◽  
Author(s):  
M. Kamran Joyo ◽  
Yarooq Raza ◽  
S. Faiz Ahmed ◽  
M. M. Billah ◽  
Kushsairy Kadir ◽  
...  
Keyword(s):  
Upper Limb ◽  
Pid Controller ◽  
Degrees Of Freedom ◽  
Optimization Technique ◽  
Pid Controllers ◽  
Proportional Integral Derivative ◽  
Effective Response ◽  
Upper Limb Rehabilitation ◽  
Proportional Integral ◽  
Limb Rehabilitation

This paper proposes a nature inspired, meta-heuristic optimization technique to tune a proportional-integral-derivative (PID) controller for a robotic arm exoskeleton RAX-1. The RAX-1 is a two-degrees-of-freedom (2-DOFs) upper limb rehabilitation robotic system comprising two joints to facilitate shoulder joint movements. The conventional tuning of PID controllers using Ziegler-Nichols produces large overshoots which is not desirable for rehabilitation applications. To address this issue, nature inspired algorithms have recently been proposed to improve the performance of PID controllers. In this study, a 2-DOF PID control system is optimized offline using particle swarm optimization (PSO) and artificial bee colony (ABC). To validate the effectiveness of the proposed ABC-PID method, several simulations were carried out comparing the ABC-PID controller with the PSO-PID and a classical PID controller tuned using the Zeigler-Nichols method. Various investigations, such as determining system performance with respect to maximum overshoot, rise and settling time and using maximum sensitivity function under disturbance, were carried out. The results of the investigations show that the ABC-PID is more robust and outperforms other tuning techniques, and demonstrate the effective response of the proposed technique for a robotic manipulator. Furthermore, the ABC-PID controller is implemented on the hardware setup of RAX-1 and the response during exercise showed minute overshoot with lower rise and settling times compared to PSO and Zeigler-Nichols-based controllers.

The Parameterization of All Plants Stabilized by a PID Controller

2013 ◽  
Vol 534 ◽  
pp. 173-181 ◽  
Author(s):  
Takaaki Hagiwara ◽  
Kou Yamada ◽  
An Chinh Hoang ◽  
Satoshi Aoyama
Keyword(s):  
Pid Controller ◽  
Industrial Applications ◽  
Pid Controllers ◽  
Proportional Integral Derivative ◽  
Proportional Integral

In this paper, we examine the parameterization of all plants that can be stabilizedby a Proportional–Integral–Derivative (PID) controller. The PID controller structure is themost widely used controller structure in industrial applications. Recently, if stabilizing PIDcontrollers for the plant exist, the parameterization of all stabilizing PID controllers was considered.However, the parameterization of all plants that can be stabilized by a PID controllerhas not been examined. In this paper, we clarify this question. In addition, we present theparameterization of all stabilizing PID controllers for plants that can be stabilized by a PIDcontroller.

Development of Proportional–Integral–Derivative and Fuzzy Control Strategies for Navigation in Agricultural Environments

2017 ◽  
Vol 140 (6) ◽  
Author(s):  
Stephanie Bonadies ◽  
Neal Smith ◽  
Nathan Niewoehner ◽  
Andrew S. Lee ◽  
Alan M. Lefcourt ◽  
...  
Keyword(s):  
Fuzzy Logic ◽  
Food Quality ◽  
Pid Controller ◽  
Fuzzy Logic Controller ◽  
Control Strategies ◽  
Working Hours ◽  
Quality And Safety ◽  
Proportional Integral Derivative ◽  
Proportional Integral ◽  
Food Quality And Safety

Farming and agriculture is an area that may benefit from improved use of automation in order to increase working hours and improve food quality and safety. In this paper, a commercial robot was purchased and modified, and crop row navigational software was developed to allow the ground-based robot to autonomously navigate a crop row setting. A proportional–integral–derivative (PID) controller and a fuzzy logic controller were developed to compare the efficacy of each controller based on which controller navigated the crop row more reliably. Results of the testing indicate that both controllers perform well, with some differences depending on the scenario.

scholarly journals MODELLING OF ACTIVE SUSPENSION SYSTEM FOR QUARTER CAR (PID CONTROL, MATLAB)

2021 ◽  
Vol 5 (10) ◽  
Author(s):  
Danish Saifi ◽  
Pramod Kumar
Keyword(s):  
Pid Control ◽  
Pid Controller ◽  
Active Suspension ◽  
Suspension System ◽  
Modelling And Simulation ◽  
Pid Controllers ◽  
Proportional Integral Derivative ◽  
Control Loop ◽  
Proportional Integral ◽  
Fine Control

We are discussing active suspension in this research. It also includes an actuator or controller (ECU), wheels and body. The rider feels comfort in travelling due to the use of these types of suspension. Because it controls vertical moments or moves of the wheels and stable rider or passenger. It is most important in the automobile industries. There are many types of controllers used for fine control to vibration caused by wheels. E.g., PID controllers, it stands for Proportional Integral Derivative. PID controller provides better simultaneous vibration of the output of the control loop. It also used for improving the performance of the suspension system. We can do modelling and simulation carried out in MATLAB software for active suspension.

scholarly journals PERANCANGAN AUTOPILOT LATERAL-DIREKSIONAL PESAWAT NIRAWAK LSU-05 (THE DESIGN OF THE LATERAL-DIRECTIONAL AUTOPILOT FOR THE LSU-05 UNMANNED AERIAL VEHICLE)

2018 ◽  
Vol 15 (2) ◽  
pp. 93 ◽  
Author(s):  
Muhammad Fajar ◽  
Ony Arifianto
Keyword(s):  
State Space ◽  
Linear Model ◽  
Unmanned Aerial Vehicle ◽  
Pid Controller ◽  
Settling Time ◽  
Proportional Integral Derivative ◽  
Proportional Integral ◽  
Directional Motion ◽  
Aerial Vehicle ◽  
Simulation Results

The autopilot on the aircraft is developed based on the mode of motion of the aircraft i.e. longitudinal and lateral-directional motion. In this paper, an autopilot is designed in lateral-directional mode for LSU-05 aircraft. The autopilot is designed at a range of aircraft operating speeds of 15 m/s, 20 m/s, 25 m/s, and 30 m/s at 1000 m altitude. Designed autopilots are Roll Attitude Hold, Heading Hold and Waypoint Following. Autopilot is designed based on linear model in the form of state-space. The controller used is a Proportional-Integral-Derivative (PID) controller. Simulation results show the value of overshoot / undershoot does not exceed 5% and settling time is less than 30 second if given step command. Abstrak Autopilot pada pesawat dikembangkan berdasarkan pada modus gerak pesawat yaitu modus gerak longitudinal dan lateral-directional. Pada makalah ini, dirancang autopilot pada modus gerak lateral-directional untuk pesawat LSU-05. Autopilot dirancang pada range kecepatan operasi pesawat yaitu 15 m/dtk, 20 m/dtk, 25 m/dtk, dan 30 m/dtk dengan ketinggian 1000 m. Autopilot yang dirancang adalah Roll Attitude Hold, Heading Hold dan Waypoint Following. Autopilot dirancang berdasarkan model linier dalam bentuk state-space. Pengendali yang digunakan adalah pengendali Proportional-Integral-Derivative (PID). Hasil simulasi menunjukan nilai overshoot/undershoot tidak melebihi 5% dan settling time kurang dari 30 detik jika diberikan perintah step.

Dynamic modeling, system identification and comparative study of various control strategies for a spatial parallel manipulator

2021 ◽  
pp. 095965182110320
Author(s):  
Mervin Joe Thomas ◽  
Shoby George ◽  
Deepak Sreedharan ◽  
ML Joy ◽  
AP Sudheer
Keyword(s):  
Real Time ◽  
Parallel Manipulator ◽  
Control Strategies ◽  
Proportional Integral Derivative ◽  
Real Time Control ◽  
Model Predictive Controller ◽  
End Effector ◽  
Proportional Integral ◽  
Time Control ◽  
Predictive Controller

The significant challenges seen with the mathematical modeling and control of spatial parallel manipulators are its difficulty in the kinematic formulation and the inability to real-time control. The analytical approaches for the determination of the kinematic solutions are computationally expensive. This is due to the passive joints, solvability issues with non-linear equations, and inherent kinematic constraints within the manipulator architecture. Therefore, this article concentrates on an artificial neural network–based system identification approach to resolve the complexities of mathematical formulations. Moreover, the low computation time with neural networks adds up to its advantage of real-time control. Besides, this article compares the performance of a constant gain proportional–integral–derivative (PID), variable gain proportional–integral–derivative, model predictive controller, and a cascade controller with combined variable proportional–integral–derivative and model predictive controller for real-time tracking of the end-effector. The control strategies are simulated on the Simulink model of a 6-degree-of-freedom 3-PPSS (P—prismatic; S—spherical) parallel manipulator. The simulation and real-time experiments performed on the fabricated manipulator prototype indicate that the proposed cascade controller with position and velocity compensation is an appropriate method for accurate tracking along the desired path. Also, training the network using the experimentally generated data set incorporates the mechanical joint approximations and link deformities present in the fabricated model into the predicted results. In addition, this article showcases the application of Euler–Lagrangian formalism on the 3-PPSS parallel manipulator for its dynamic model incorporating the system constraints. The Lagrangian multipliers include the influence of the constraint forces acting on the manipulator platform. For completeness, the analytical model results have been verified using ADAMS for a pre-defined end-effector trajectory.

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