SciELO

DEEP LEARNING-DRIVEN PREDICTIVE CONTROL METHOD FOR OPTIMIZING COMBINE HARVESTER OPERATION SPEED

To enhance the automation and efficiency of combine harvesters, this paper proposes a predictive control method based on Long Short-Term Memory (LSTM) neural networks. The method integrates ...
IEEE

Predictive PID Control for Automated Guided Vehicles Using Genetic Algorithm and Machine Learning

Abstract: The integration of automated guided vehicles (AGVs) in industrial automation demands precise and adaptive control systems for efficient path tracking. This study introduces a hybrid ...
Nature

Novel multiagent reinforcement learning framework using twin delayed deep deterministic policy gradient for adaptive PID control in boiler turbine systems

The latest developments in industrial control applications emphasize the need for incorporating intelligent algorithms for enhanced adaptability and performance. This study addresses the challenge of ...
Frontiers

Learning-based control for tendon-driven continuum robotic arms

Tendon-Driven Continuum Robots are widely recognized for their flexibility and adaptability in constrained environments, making them invaluable for most applications, such as medical surgery, ...
LinkedIn

Precision in Motion: Mastering Servo Tuning & PID Optimization in Siemens TIA Portal

In the world of high-speed automation, motion control isn’t just a feature—it’s the foundation. From robotic arms on automotive lines to micro-precision in semiconductor fabrication, everything ...
Automation World

AI In My PID Loops? It’s More Likely Than You’d Expect

Some wonder if AI will replace PID control loops. The reality is that, instead of replacing PID, AI is stepping in to help keep things running smoothly without upending regulatory trust. Think of AI ...
Nature

Optimized PID controller and model order reduction of reheated turbine for load frequency control using teaching learning-based optimization

There is a fast-expanding demand for a better-quality electric power supply. Water’s kinetic energy and fossil fuels’ thermal energy are well-known sources of electric energy. The primary component of ...
Scientific Research Publishing

Predictive Analytics for Project Risk Management Using Machine Learning ()

1 Pharmavite LLC, Los Angeles, CA, USA. 2 Microsoft, Charlotte, NC, USA. 3 AXS Group LLC, Los Angeles, CA, USA. 4 TCS, Indianapolis, IN, USA. Risk management is relevant for every project that which ...
Frontiers

Design and Validation of Reversing Assistant Based on Extreme Learning Machine

As an important function of the advanced driver assistance system (ADAS), the reversing assistant (RA) achieves trajectory retracing by applying accurate position estimation and tracking control. To ...
IEEE

PID Controller Machine Learning Algorithm Applied to the Mathematical Model of Quadrotor Lateral Motion

Abstract: The paper discusses the problem of automatic tuning of the PID controller. The auto-tuning algorithm of the PID controller based on one machine learning method, which is equivalent to the ...