Results 61 to 70 of about 12,056 (184)
Improved model reduction and tuning of fractional-order PI(λ)D(μ) controllers for analytical rule extraction with genetic programming [PDF]
This is the author accepted manuscript. The final version is available from Elsevier via the DOI in this record.Genetic algorithm (GA) has been used in this study for a new approach of suboptimal model reduction in the Nyquist plane and optimal time ...
Das, S, Das, S, Gupta, A, Pan, I
core +1 more source
A low‐cost, self‐driving laboratory is developed to democratize autonomous materials discovery. Using this "frugal twin" hardware architecture with Bayesian optimization, the platform rapidly converges to target lower critical solution temperature (LCST) values while self‐correcting from off‐target experiments, demonstrating an accessible route to data‐
Guoyue Xu, Renzheng Zhang, Tengfei Luo
wiley +1 more source
FRACTIONAL ORDER PROPORTIONAL-INTEGRAL-DIFFERENTIAL BASED CONTROLLER DESIGN FOR DC MOTOR SPEED CONTROL [PDF]
Fractional order calculus has become a growing area in the field of control theory. This phenomenon allows us to describe and model a real object more accurately than the conventional “integer” methods.
Prof. Ashok M. Jain, Sanket Hari Nankar
core +4 more sources
Fractional Order Internal Model PID Control for Pulp Batch Cooking Process
Pulp batch cooking is performed in a sealed high-temperature and high-pressure digester and is a complex black-box process. Based on the analysis of the mechanism of batch cooking, a model with nonlinear characteristics was established.
Wenjuan Shan, Yifeng Wang, Wei Tang
doaj +1 more source
An optimized fractional order PID controller for suppressing vibration of AC motor [PDF]
Fractional order Proportional-Integral-Derivative (PID) controller is composed of a number of integer order PID controllers. It is more accurate to control the complex system than the traditional integer order PID controller.
Chang Dong +4 more
core +2 more sources
This study introduces a data‐driven framework that combines deep reinforcement learning with classical path planning to achieve adaptive microrobot navigation. By training a surrogate neural network to emulate microrobot dynamics, the approach improves learning efficiency, reduces training time, and enables robust real‐time obstacle avoidance in ...
Amar Salehi +3 more
wiley +1 more source
This paper studies operator and fractional order nonlinear robust control for a spiral counter-flow heat exchanger with uncertainties and disturbances.
Guanqiang Dong, Mingcong Deng
doaj +1 more source
Adaptive Macroscopic Ensemble Allocation for Robot Teams Monitoring Spatiotemporal Processes
We propose an online, environment feedback‐driven macroscopic ensemble approach to adapt robot team task allocation in spatiotemporal environments by controlling robot populations rather than assigning individual robots, all while maintaining robust team performance even for small teams. Our simulation and experimental results show better or comparable
Victoria Edwards +2 more
wiley +1 more source
Design and Implementation of Novel Fractional-Order Controllers for Stabilized Platforms
As a position servo system to isolate disturbance from its carrier, stabilized platform requires high-precision and high-adaptability control. However, conventional integer-order PID (IOPID) control fails to meet that requirement.
Jie Zhang +6 more
doaj +1 more source
General type industrial temperature system control based on fuzzy fractional-order PID controller
A fuzzy fractional-order PID control algorithm for a general type industrial temperature control system is proposed in this paper. In order to improve the production quality and controlled model accuracy, a fractional-order elementary system is used to ...
Lu Liu, Dingyu Xue, Shuo Zhang
doaj +1 more source

