Implementation Of Proportional Integral Derivative Controller Research Articles

Modeling and Implementation of PID Controller in Vehicle Ride Comfort Improvement Using Bond Graph

The proportional integral derivative (PID) controller method is a famous and influential approach used in a variety of engineering domain systems. This paper presents Bond Graph modelling and implementation of PID controller in the active quarter-vehicle suspension system for the purpose of achieving better ride comfort. Bond graph is a better tool for modelling multi-domain energy systems with control hardware associated with it. SYMBOL SHAKTI software is used to simulate the active vehicle suspension system, which is theoretically represented as a 4-DOF human Bio-dynamic model combined with a 3-DOF quarter automobile system. The suggested PID Controller's performance is contrasted with that of the passive model. To measure the effectiveness of the suggested PID controller suspension system, time domain evaluations of systems performance criteria are conducted. The findings show that a significant improvement in ride comfort is offered by the suggested Bond graph PID controller model of the active vehicle suspension.

Implementation of PID controller and enhanced red deer algorithm in optimal path planning of substation inspection robots

AbstractIn contemporary power transmission systems, substation monitoring stands as a vital but challenging task. While robotics offers promise in this regard, its potential is still nascent, struggling to replicate human intelligence. This article's core aim was to optimize robot path planning (RPP). Employing the enhanced red deer algorithm (ERDA), we sought to bolster RPP for more efficient substation inspections. The key methods used seem to be modeling, experimentation, comparative analysis, and some elements of data benchmarking to systematically evaluate and validate their proposed technique and models both in simulation and the real world. Research aims to enhance substation inspection effectiveness and bolster the safety of power usage in society. Proposed hybrid approach, combining proportional–integral–derivative (PID) with ERDA (PID–ERDA), underpins an Intelligent Intelligent RPP framework tailored to substation inspections. Examining the PID–ERDA model's performance, it significantly improved path length by 18%–29% and reduced response times by 14%–26% compared with PID or ERDA alone. PID–ERDA consistently achieved optimal solutions in 40–60 trials out of 85, while PID and ERDA managed 20–40 trials with inconsistent optimization. Additionally, it reduced average response times to 17–20 s from 21 to 27 s observed when using PID and ERDA separately. PID–ERDA also demonstrated superior path accuracy, surpassing methods like improved adaptive control algorithm‐feedforward neural network, enhanced unified algorithm‐susceptible‐infected‐removed, and bounded behavior‐particle swarm optimization by 7%–13%. The study affirms that the PID–ERDA model significantly enhances path planning for substation inspections, representing a milestone in RPP for power station inspections within modern power transmission systems. The primary contribution of this research is the significant improvement it brings to RPP for power station inspections, especially in substation monitoring within modern power transmission systems.

Implementation of Parallel Navigation and PID Controller for Drone Swarm Pursuit

The usage of a drone in pursuit has been researched quite extensively, but with only one drone, the pursuit suffers from sensory limitations where sensors are either expensive or have limited capabilities. In this paper, a drone swarm controller system for pursuit is developed to solve the problem based on Parallel Navigation (PN) and Proportional-Integral-Derivative (PID). The controller consists of two main parts with different functions, each in charge of navigation and control modulation. Navigation is performed by a High-Level Controller built on PN, which allows navigation toward an object while avoiding obstacles simultaneously. Control modulation is performed by a Low-Level Controller based on a PID controller. The implementation study is then performed in a simulated environment with varying swarm members. Results show that the controller system successfully coordinated the drone swarm to surround the target after it is found, and pursuit with more drones consistently locates the target faster.

Implementation of Fuzzy PID Controller in Cascade with Anti-Windup to Real-Scale Test Equipment for Pavements

In the industry and academia, large-scale equipment has been developed, which requires control systems that provide safety and efficiency with the lowest possible energy consumption. In the industrial cascade control system, nested controllers have been a versatile tool for the control of large-scale equipment. Research shows that these types of controllers improve their performance with the integration of artificial intelligence algorithms and prevention methods against controller saturation. For this reason, this paper presents the development of a fuzzy proportional-integral-derivative (PID) controller in cascade with anti-windup (AW) for full-scale test equipment for pavements. In this study, the mathematical expressions for the equipment, the design of the controller and additional systems for comparison, simulation and analysis are developed. The main objective is to test the functionality of this type of nested controllers for these systems.

Real-Time implementation and performance analysis of robust 2-DOF PID controller for Maglev system using pole search technique

In recent times, Magnetic Levitation (Maglev) technology has gained huge popularity in different fields of research. Transportation, nuclear, aerospace, biomedical, civil and electrical engineering are some of the areas where the presence of Maglev technology is prominent. But because of the inherent nonlinear and unstable behaviour, the task of designing a suitable controller becomes very challenging for the control engineers. In this paper, a simple but effective approach has been proposed for the design of 2-DOF Proportional-Integral-Derivative (PID) controller for the control of Maglev system in simulation and real-time for the very first time, to the best of author's knowledge. The controller parameter values have been analytically obtained by optimizing the location of closed loop poles in the s-plane which eventually minimizes the Integral Square Error (ISE) of the closed loop system along with the controller. As the controller parameters are found by searching the best pole location, we name it as pole search technique. The performance of the controller has been compared with those of the 1 & 2-DOF Integer Order and Fractional Order PID and I-PD controllers designed for the same Maglev plant. The result of the comparison reveals that the 2-DOF PID controller, designed in this paper, outperforms other controllers in terms of maximum overshoot, settling time, Integral Absolute Error (IAE), Integral Time Absolute Error (ITAE) and Integral Time Square Error (ITSE). Moreover, to illustrate the loop robustness property, input and output disturbances have been applied in real-time simulation environment and sensitivity and complementary sensitivity analysis have been performed. Additionally, to show the applicability of the proposed technique apart from Maglev, 2-DOF PID controller has been designed for the Ball and Beam and Coupled Tank system and their performance has been compared with the existing results.

Design and implementation of EP-based PID controller for chaos synchronization of Rikitake circuit systems

This article addresses an evolutionary programming (EP) algorithm technique-based and proportional-integral-derivative (PID) control methods are established to guarantee synchronization of the master and slave Rikitake chaotic systems. For PID synchronous control, the evolutionary programming (EP) algorithm is used to find the optimal PID controller parameters kp, ki, kd by integrated absolute error (IAE) method for the convergence conditions. In order to verify the system performance, the basic electronic components containing operational amplifiers (OPAs), resistors, and capacitors are used to implement the proposed chaotic Rikitake systems. Finally, the experimental results validate the proposed Rikitake chaotic synchronization approach.

Implementation of Multimodel-Based PID and Intelligent Controller for Simulated and Real-Time Temperature Control of Injection Molding Machine

The proposed real-time multimodel for the injection molding process mainly contributes to the barrel temperature control. Good control of the plastic melt temperature is very important for injection molding in reducing the operator setup time, ensuring product quality, and preventing thermal degradation of the melt. The controllability and set points of the barrel temperature also depend on the precise monitoring and control of the plastic melt temperature. Motivated by the practical temperature control of injection molding, this article proposes a multimodel-based proportional integral derivative (PID) control scheme in real-time and the simulation studies of the PID, fuzzy, and adaptive neuro fuzzy inference system (ANFIS) control schemes. The injection molding process consists of three zones, and the mathematical model for each zone is different. The control output for each zone controller is assigned a weight, based on the computed probability of each model, and the resulting action is the weighted average of the control moves of the individual zone controller.

Implementation of Fuzzy and PID Controller to Water Level System using LabView

paper is about the water level control system which is required in many industrial processes like water treatment plant, the idea of the process is to keep the tank water level at the desired set point. First we implemented the conventional proportional - integral - derivative (PID) controller to eliminate the steady state error, then it was used Fuzzy logic controllers which gives more performance and stability. It is noted from the results that the Fuzzy Logic controller is more enhanced than PID controller in which its no overshoot, faster settling time, better set point tracking and produced lower performances like integral of time and absolute error (ITAE) integral of time and squared error (ITSE),and integral absolute error (IAE), integral squared error (ISE). Both PID and fuzzy controller are implemented using LabView software Keywordsroportional-integral-derivative (PID) controller, Fuzzy Controller, LabView

Stabilization and Control of an Autonomous Quadcopter

A Quadcopter is a helicopter which has four equally spaced rotors, usually arranged at the corners of a square body. Due to four independent rotors, the need for a swashplate mechanism is palliated. The swashplate mechanism was required to allow the helicopter to utilize more degrees of freedom, but the same level of control could be obtained by adding two more rotors. The development of Quadcopter was stalled until very recently, because controlling four independent rotors was proven to be incredibly difficult and impossible without electronic assistance which has made even completely autonomous control of quadcopters feasible for commercial, military, and even hobbyist purposes. The paper offers dynamic simulation of brushless DC motor speed control used in a quadcopter and also focuses on design and implementation of PID (Proportional-Integral-Derivative) controller through simulation for proper controlling of altitude roll and pitch in a quadcopter. The effectiveness of proposed controller can be analyzed by considering the performances of peak time, settling time and overshoots for various set point changes in the throttle movements. All simulation studies have been carried out using the MATLAB software.

Design and Implementation of Optimal Fuzzy PID Controller for DC Servo Motor

A method is proposed for improving the transient positioning response of a DC servo motor controlled by a proportional- integral-derivative (PID) controller. In the proposed approach, the optimal gains of the PID controller are determined using an Evolutionary Programming (EP) scheme and a Genetic Algorithm (GA), respectively, based on an integrated-absolute error (IAE) fitness function. The optimal gain constants obtained using the two methods a re then fine tuned using a Fuzzy Logic Controller (FLC). The experimental results show that the FLC controller yields an effective improvement in the positioning response of the DC servo motor compared to that obtained using the optimized PID controller alone. In addition, it is shown that the FLC + EP based PID controller provides a more rapid response than the FLC + GA based PID controller. The effectiveness of proposed controllers is verified experimentally.

Performance Analysis and FPGA Implementation of Digital PID Controller for Speed Control of DC Motor

This paper deals with the performance analysis and implementation of PID(Proportional-Integral-Derivative) Controller on FPGA platform.The hardware implementation has been done on Xilinx Spartan 3E FPGA board.The software implementation has been done using Xilinx ISE 8.1i as a tool and simulation is performed using ModelSim 5.4a as a simulator.The PWM signal is generated by FPGA board,which further given to dc motor for its speed control. A new technique has been introduced for the generation of the control input as a PWM signal for controlling the motor driver circuit and decoding the optical encoder data for using it for the speed feedback in the PID control loop. The VHDL algorithm for the proposed implementation has been presented in this paper. Performance analysis of PID controller using MATLAB software shows the effectiveness of the proposed method.

Minimum delay PID control of interpolated joint trajectories of robot manipulators

The digital implementation of an optimal PID (proportional integral derivative) controller of linearly interpolated joint trajectories is presented. The controller obtains optimal performance by reformulating the PID control law to minimize the time delay between the position transducer reading and the application of the corrective torque. Compared with the PID controller that is computed in a straightforward fashion, this formulation reduces the time delay by a factor of three. The superior performance of the proposed minimum-delay PID (MD PID) is demonstrated by experiments on a robot manipulator. Other practical issues associated with a digital PID control of joint trajectories of a robot manipulator, such as integer overflow and compensation for dynamics and joint-friction, are discussed. >