Achieving precision in PID tuning yields remarkable outcomes, such as increased system efficiency, responsiveness, and overall operational performance

PID tuning represents a key aspect of control systems, influencing the performance and stability of diverse industries' operations. By adjusting the proportional, integral, and derivative constants, a PID controller minimizes error and ensures the control variable aligns with dynamic system changes.

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With its intuitive visual representation and logical structure, ladder logic resembling to electrical relay circuits, ladder logic programming has become a standard in the field to develop complex control systems

Modern industrial automation demands robust and reliable control systems. Ladder logic programming is a cornerstone of PLC-based automation, combining traditional relay logic with advanced digital capabilities. This guide explores everything engineers should know about ladder logic programming

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Robotic arms in the industry based on PID loop 

This guide delves into the basics and components of PID control, implementation, application examples, impacts, challenges, and solutions aiming to provide readers with a thorough understanding of this integral concept.

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This article offers an in-depth view of process control, including its history, fundamental concepts, components, strategies, and implementation in industrial systems. 

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This article is a part of&nbsp;our&nbsp;<a href="http://www.wevolver.com/student-program" id="isPasted" target="_blank">University Technology Exposure Program</a>. The program aims to recognize and reward innovation from engineering students and researchers across the globe.<h2 dir="ltr" id="isPasted">Introduction</h2>The introduction of automobiles into the world inculcated innovation in many aspects of engineering, including design and manufacturing. Engineers worldwide continuously strive to develop cutting-edge technologies to augment the riders’ comfort traffic behavior and enhance safety and fuel economy. In the current scenario, advanced features, including forward collision, traction control, and lane change, augment the safety, whereas the fuel economy drive mode reduces the fuel consumption. &nbsp;Abbreviations:<div align="left" dir="ltr"><table><tbody><tr><td>ACC</td><td>Adaptive Cruise Control</td><td>ESC</td><td>Engine Speed Caliber</td></tr><tr><td>ACCSSP</td><td>Adaptive cruise control set speed profile (MPH)</td><td>IAS</td><td>Initial ACC Speed (MPH)&nbsp;</td></tr><tr><td>CAT</td><td>Cabin air temperature (℉)&nbsp;</td><td>IES</td><td>Instantaneous Engine Speed (rad/s)&nbsp;</td></tr><tr><td>DL</td><td>Deep Learning&nbsp;</td><td>IET</td><td>Instantaneous Engine Torque (Nm)&nbsp;</td></tr><tr><td>EAT</td><td>External air temperature (℉)&nbsp;</td><td>IFCR</td><td>Instantaneous Fuel Consumption Rate ( 1E-8m3s-1)</td></tr><tr><td>ED</td><td>Euclidean Distance—Ideal EOP and Predicted EOP&nbsp;</td><td>LAT</td><td>Lateral acceleration &nbsp;( m.s-2)</td></tr><tr><td>EOC</td><td>Engine Operating Conditions</td><td>LOT</td><td>Longitudinal acceleration ( m.s-2)</td></tr><tr><td>EOP</td><td>Engine Operating Point&nbsp;</td><td>VLV</td><td>Vehicle level vectors</td></tr><tr><td>ETC</td><td>Engine Torque Caliber &nbsp;</td><td>YAR</td><td>Yaw rate (rad/s)</td></tr></tbody></table></div>Among the features integrated into the vehicle, the ACC system developed by [Labuhn and Chundrlik, 1995] played a vital dual role in affecting safety and EOC. The intricate concept of the ACC system is to produce controlled acceleration without disengaging the cruise in the user-defined proximity and strictly follow the user command of set speed. &nbsp;Also, we could conclude from the existing literature that activation of ACC results in lower fuel consumption. Therefore activating the ACC feature for traversing long trips would augment EOC.&nbsp;However, identifying the optimal ACCSSP by considering the dynamic state of the vehicle for a definite coordinate on the terrain is an unsolved, challenging task for engineers. Existing techniques rely on either one or two affecting factors as inputs to predict ACCSSP considered, but none of the researchers included all the factors in conjunction to the best of our knowledge.&nbsp;<h2 dir="ltr">Predicting the optimal ACCSSP by optimizing the EOC</h2>This research presents a novel methodology to predict the optimal adaptive cruise control set speed profile (ACCSSP) by optimizing the engine operating conditions (EOC) considering vehicle level vectors (VLV) (age, body parameters, environment, driver behavior) as the affecting parameters excluding traffic congestion information. This work investigates engine operating conditions (EOC) criteria to develop a predictive model of ACCSSP in real-time. We used real-world field data obtained from Cadillac test vehicles driven (retrieved from Controller area network) by activating the ACC feature for developing the DL model. We developed a deep learning (DL) model using the NARX method to predict engine operating points (EOP - IET, IES, IFCR) mapping the VLV as shown in Figure 1. The conformance between the actual and predicted values validates the performance of the DL model, as shown in Figure 2.&nbsp;<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNjQ1NzEwODM4MjM1LTE2NDU3MTA4MzgyMzUucG5nIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==" class="fr-fic fr-dii" alt="eop-predictive-model-input-output">Fig. 2: Predictive model of EOP - Inputs and Outputs<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNjQ1NzEwODM4NzcyLTE2NDU3MTA4Mzg3NzIucG5nIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==" class="fr-fic fr-dii" alt="eop-prediction">Fig. 2: Prediction of EOP - ACCSSP = 70 MPH, 2019 Cadillac XT6We used a realistic set of assumptions to estimate the VLV for the future time steps for the range of allowable speed values and applied them at the input of the developed DL model to generate multiple sets of EOP’s. We imposed the defined EOC criteria on these EOPs, and the top three modes of speeds satisfying all the requirements are derived at each second.&nbsp;Thus, three eligible speed values in the user-defined range are estimated for each second, and an additional criterion is defined to generate a unique ACCSSP for future time steps, as shown in Figure 3. A performance comparison between predicted and constant ACCSSP’s indicates that the predictive model outperforms constant ACCSSP.<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNjQ1NzEwODM4MDA5LTE2NDU3MTA4MzgwMDkucG5nIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==" class="fr-fic fr-dii" alt="accssp-prediction">Fig. 3: Process - Prediction of ACCSSP<h2 dir="ltr">Results</h2>The plot of constant and predicted ACCSSP is shown in Figure 4. The engine performance was defined by the euclidean distance of the operating and ideal EOP (ED) and engine torque and speed caliber [ETC, ESC]. The measure of these parameters for the predicted and constant ACCSSP is shown in Figure 5.&nbsp;<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNjQ1NzEwODM4MTIyLTE2NDU3MTA4MzgxMjIucG5nIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==" class="fr-fic fr-dii" alt="predicted-ACCSP">Fig. 4: Predicted ACCSSP - Initial ACC Speed = 70 MPH, Cadillac XT6<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNjQ1NzEwODM4NDQzLTE2NDU3MTA4Mzg0NDMucG5nIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==" class="fr-fic fr-dii" alt="eoc-parameters">Fig. 5: EOC Parameters - [ETC, ESC, ED], Cadillac XT6<h2 dir="ltr">Conclusion</h2>This novel algorithm could potentially act as a new feature in the vehicle which enhances the vehicle performance obliging the command of the driver.&nbsp;<h2 dir="ltr">About the University Technology Exposure Program 2022</h2>Wevolver, in partnership with <a href="https://mouser.com/" target="_blank">Mouser Electronics</a> and&nbsp;<a href="https://www.ansys.com/" rel="nofollow" target="_blank">Ansys</a>, is excited to announce the launch of the University Technology Exposure Program 2022. The program aims to recognize and reward innovation from engineering students and researchers across the globe. Learn more about the program <a href="http://www.wevolver.com/student-program" target="_blank">here</a>.<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNjQ1NzEwODM4MjgzLTE2NDU3MTA4MzgyODMucG5nIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==" class="fr-fic fr-dii" alt="university-technology-exposure-program-mouser-ansys"><h2 dir="ltr">References</h2>Kolachalama S, Malik H. Predictive Model of Adaptive Cruise Control Speed to Enhance Engine Operating Conditions. Vehicles. 2021; 3(4):749-763. https://doi.org/10.3390/vehicles304004

This research predicts the adaptive cruise control set speed profile in the user-defined range for the future time steps, optimizing the engine operating point (EOP) in real-time. The prediction of EOP was made by a deep learning model using all the parameters affecting the engine performance. 

adaptive control

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Predictive Model of Adaptive Cruise Control Speed to Enhance Engine Operating Conditions

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