Tuning stochastic local search algorithms for tackling large instances is difficult due to the large amount of CPU-time that testing algorithm configurations requires on such large instances. We define an experimental protocol that allows tuning an algorithm on small tuning instances and extrapolating from the obtained configurations a parameter setting that is suited for tackling large instanc...

Penalized regression models are popularly used in high-dimensional data analysis to conduct variable selection and model fitting simultaneously. Whereas success has been widely reported in literature, their performances largely depend on the tuning parameters that balance the trade-off between model fitting and model sparsity. Existing tuning criteria mainly follow the route of minimizing the e...

Adaptive PID controller based on real base function (RBF) network identification by optimal tuning of proportional– integral–derivative (PID) controller parameter is necessary for thematic factory operation of an automatic voltage regulator (AVR) system. This study presents a combined genetic algorithm (GA) and real base function network (RBF) identification control approach to determine the op...

Matlab-SIMULINK based real time temperature control of oven using different kinds of auto-tuning PID (Proportional-Integral-Derivative) methods is presented in this paper. Ziegler Nichols Step Response Method (P,PI), Relay Tuning Method (P,PI) and Integral Square Time Error (ISTE) disturbance criterion (PI) method are used to control temperature of the experiment set. Controller parameters are ...

This paper discusses PID controller tuning for integrating processes with time-delay and first order lag. Most of the existing tuning rules for this kind of processes have the same general structure, and the properties of these rules are discussed especially in connection with varying time-delay systems. The paper proposes a novel tuning method that optimizes the closed-loop performance with re...

PID controllers are widely used in industrial plants because the structure of PID controller is very simple and its control principle is very clear [1]. It is practical and very easy to be implemented. Industrial processes are subjected to variation in parameters, which when significant makes the system unstable. So the control engineers are on look for automatic tuning procedures. In this pape...

In this paper, a new Model Predictive Controller (MPC) parameters tuning strategy is proposed using a LabVIEW-based perturbed Particle Swarm Algorithm (pPSA). This original LabVIEW implementation of this metaheuristic algorithm is firstly validated on some test functions in order to show its efficiency and validity. The optimization results are compared with the standard PSO approach. The param...

In data mining, hybrid intelligent systems present a synergistic combination of multiple approaches to develop the next generation of intelligent systems. Our paper presents an integration of a Combined Multiple Models (CMM) technique with an evolutionary approach that is used for tuning of parameters. Proposed hybrid classifier was tested in microarray analysis domain. This domain was chosen i...

Tuning and calibration are processes for improving the representativeness of a computer simulation code to a physical phenomenon. This article introduces a statistical methodology for simultaneously determining tuning and calibration parameters in settings where data are available from a computer code and the associated physical experiment. Tuning parameters are set by minimizing a discrepancy ...

The central air condition system is a complex system. Aimed at the puzzle of optimal status adjusting by once setting parameter of fuzzy PID, the paper proposed a sort of parameter auto-tuning method of fuzzy-PID based on self-learning algorithm. It adopted parameter autotuning technique to adjust the PID parameters in real time so as to ensure good quality of control system. It combined fuzzy ...