In this paper we propose a method for optimization of closed-loop parameters and continuous-time sampling period by digital self-tuning PID control of pressure plant. The quality of pressure plant control is experimentally compared between two modifications of digital self-tuning PID controllers. The results of adaptive pressure plant control show that the optimization of closed-loop parameters...

FM-AFM is an extremely powerful and versatile imaging technique capable of atomic resolution imaging in vacuum, air or liquid. However, obtaining such results in practice currently requires tedious and time consuming manual tuning of many feedback parameters by trial and error. We present a recently developed algorithm for automated tuning of FM-AFM feedback parameters. The algorithm optimizes ...

In the paper, a new flexible modification of neofuzzy neuron, neuro-fuzzy network based on these neurons and adaptive learning algorithms for the tuning of their all parameters are proposed. The algorithms are of interest because they ensure the on-line tuning of not only the synaptic weights and membership function parameters but also forms of these functions that provide improving approximati...

In this paper, we explore hidden persistent homological structures in sparse regressions. Sparse regressions are usually parameterized by tuning parameters that determine the sparsity of solutions. By treating the tuning parameters as additional dimension, we can have multi-scale representations. We can show there exist hidden persistent homological structures in these dimensions. By exploiting...

Application auto-tuning has produced excellent results in a wide range of computing domains. Yet adapting an application to use this technology remains a predominately manual and labor intensive process. This paper explores first steps towards reducing adoption cost by focusing on two tasks: parameter identification and range selection. We show how these traditionally manual tasks can be automa...

This paper exhibited a survey investigation of tuning of Proportional Integral Derivative (PID) Controller for speed control of CSTR PLANT utilizing delicate processing strategies. CSTR PLANT engine is generally utilized as a part of businesses regardless of the possibility that its support cost is higher than the enlistment engine. Speed control of CSTR PLANT is pulled in extensive research an...

FM-AFM is an extremely powerful and versatile imaging technique capable of atomic resolution imaging in vacuum, air or liquid. However, obtaining such results in practice currently requires tedious and time consuming manual tuning of many feedback parameters by trial and error. We present a recently developed algorithm for automated tuning of FM-AFM feedback parameters. The algorithm optimizes ...

The widespread use of artificial neural networks and the difficult work regarding the correct specification (tuning) of parameters for a given problem are the main aspects that motivated the approach purposed in this paper. This approach employs an evolutionary search to perform the simultaneous tuning of initial weights, transfer functions, architectures and learning rules (learning algorithm ...

This paper deals with the modelling, simulation-based controller design and path planning of a four rotor helicopter known as a quadrotor. All the drags, aerodynamic, coriolis and gyroscopic effect are neglected. A Newton-Euler formulation is used to derive the mathematical model. A smart self-tuning fuzzy PID controller based on an EKF algorithm is proposed for the attitude and position contro...

In depth map generation, the settings of the algorithm parameters to yield an accurate disparity estimation are usually chosen empirically or based on unplanned experiments. A systematic statistical approach including classical and exploratory data analyses on over 14000 images to measure the relative influence of the parameters allows their tuning based on the number of bad pixels. Our approac...