Many nature-inspired optimization techniques have a number of parameters, and automated algorithm tuning has shown to be instrumental for deriving high-performing algorithms. In previous work, we have studied state-of-the-art derivative-free continuous optimization algorithms together with techniques for handling the stochasticity arising in the tuning problems to fine-tune numerical parameters...

In order to reach satisfactory performance, fault diagnosis methods require the tuning of internal parameters, usually called hyperparameters. This is generally achieved by optimizing a performance criterion, typically a trade-off between false-alarm and non-detection rates. Perturbations should also be taken into account, for instance by considering the worst possible case. A new method to ach...

Using the basic concepts and design methods of Human Simulated Intelligent Control (HSIC), we have designed the master control level of an HSIC controller for the swinging-up and handstand control of a cart-double pendulum. Then, the self-tuning structure of the self-tuning level of the HSIC Controller is implemented using fuzzy logic rules. This structure has fuzzy self-tuning abilities in the...

In this work, an auto-tuning procedure for PID controllers is presented. This autotuning procedure identifies a FOPDT model for a given process and uses an evolutionary algorithm to solve a constrained non-convex optimization problem to adjust the parameters of a PID controller with derivative filter. The auto-tuning procedure is validated with a set of process with different characteristics. P...

This paper addresses multidimensional tuning parameter selection in the context of “train-validate-test” and K-fold cross validation. A coarse grid search over tuning parameter space is used to initialize a descent method which then jointly optimizes over variables and tuning parameters. We study four regularized regression methods and develop the update equations for the corresponding descent ...

Designing of a PID controller is a very common method for industrial process control and due to its very simple and efficient function; it is used in a wide variety of industrial applications. PID controller to reduce the steady state error and dynamic response of the system is used. PID controller design is an inevitable problem in setting the coefficients need to try a lot of trial and error,...