Application of optimization algorithms to adaptive motion control for repetitive process

Low-Cost Implementation of an Adaptive Neural Network Controller for a Drive with an Elastic Shaft

This paper deals with the implementation of an adaptive speed controller applied for two electrical machines coupled by a long shaft. The two main parts of the study are the synthesis of the neural adaptive controller and hardware implementation using a low-cost system based on an STM Discovery board. The framework between the control system, the power converters, and the motors is established with an ARM device. A radial basis function neural network (RBFNN) is used as an adaptive speed controller. The net coefficients are updated (online mode) to ensure high dynamics of the system and correct work under disturbance. The results contain transients achieved in simulations and experimental tests.

Chaos Embed Marine Predator (CMPA) Algorithm for Feature Selection

Data mining applications are growing with the availability of large data; sometimes, handling large data is also a typical task. Segregation of the data for extracting useful information is inevitable for designing modern technologies. Considering this fact, the work proposes a chaos embed marine predator algorithm (CMPA) for feature selection. The optimization routine is designed with the aim of maximizing the classification accuracy with the optimal number of features selected. The well-known benchmark data sets have been chosen for validating the performance of the proposed algorithm. A comparative analysis of the performance with some well-known algorithms advocates the applicability of the proposed algorithm. Further, the analysis has been extended to some of the well-known chaotic algorithms; first, the binary versions of these algorithms are developed and then the comparative analysis of the performance has been conducted on the basis of mean features selected, classification accuracy obtained and fitness function values. Statistical significance tests have also been conducted to establish the significance of the proposed algorithm.

A Comparative Study and Optimization of Switching Functions for Sliding-Mode Observer in Sensorless Control of PMSM

The sensorless control of the permanent magnet synchronous motor (PMSM) has attracted wide attention due to its high reliability, economic and safety benefits. A fast and high-precision rotor-position estimation is inevitable for the implementation of sensorless control. Sliding-mode observer (SMO) is a preferred solution for sensorless control by many industrial companies. This article addresses the comparison of different switching functions employed in the control structure of sensorless field-oriented control with SMO. The switching functions are classified and their influence on the performance of the PMSM is verified for different shaping coefficients (SC). In addition, a statistical evaluation of the switching functions is provided to find the optimal values of SC. An experimental and statistical evaluation validated the substitutability of signum and hyperbolic switching functions and optimal values of SC have been found.

Fuzzy Adaptive Type II Controller for Two-Mass System

This paper presents original concepts of control systems for an electrical drive with an elastic mechanical coupling between the motor and the driven mechanism. The synthesis procedure of the speed controller uses a proposed quality index (cost function) of system operation ensures the minimization of both tracking errors and torsional vibrations. Proper selection of the cost function focusses more on the reduction of torsional vibrations due to their negative influence on the drive’s mechanical coupling vitality. The omission of the plant identification of an adaptive fuzzy controller was proposed. Two types of fuzzy controllers were analyzed, namely with type I and type II fuzzy membership functions. The novelty of the presented approach is in the application of a Petri transition layer in a type II fuzzy controller which reduces the numerical complexity in case of a large number of complicated type II fuzzy sets. The presented simulation and experimental results prove that the best dumping of mechanical vibrations ensures the adaptive fuzzy controller with type II functions and a Petri transition layer.