This paper presents a design of a cruise control based on a fractional-order proportional and integral (PI) direct torque control applied to the traction system of an electric vehicle (EV). The paper also discusses the modeling, control design and simulation, resulting in a numerical simulator composed of detailed models of the main components: transmission system, induction motor, power electronics, control system, and vehicle dynamics. The simulation was developed in MATLAB/Simulink and will allow the estimation of the energy consumption of an EV under specific configurations. Simulation results show the efficiency of the designed control. These simulations were carried out using the velocity profiles given by the New Europe Drive Cycle (NEDC).

In this investigation, ROS-based robust attitude control is designed for a two-wheeled self-balancing mobile robot (TWSBR) using the active disturbance rejection control (ADRC) technique. The designed ROS framework contemplates communication between topics for the desired robot commands and distributed framework design. This open architecture allows the integration of sensors, actuators, and processors. The architecture includes User-Friendly Interface, storage, navigation, control, and drivers. The low-cost robot was designed for educational purposes. It uses an Arduino Mega as a low-level processing unit, a Raspberry Pi 4 as a companion computer where high-level commands are processed, an MPU6050 Inertial Measurement Unit sensor, DC motors GW4058-555 with quadrature type encoder with two phases, the VNH2SP30 controller module used as the power stage and a Lithium Polymer (Li-Po) battery (11.1 V, 2200 mah) is used as the power source. The robust control algorithm is designed through the ADRC methodology based on the extended state observer (ESO). The ESO simultaneously estimates external disturbances, model uncertainties, and unmodeled dynamics such as friction, engine wear, and tire slippage. The stability of the developed controller is analyzed via the Lyapunov stability theory. Real-time experimental results are carried out under the regulation and rejection of external disturbances. The control algorithm is light and easy to implement and adjust in integrated systems with low computer resources.

This manuscript describes a swift control prototyping (SCP) approach implemented within an industrial setting, utilizing a DC-DC nonlinear quadratic buck converter (QBC) to decrease production expenses of electronic materials and devices while improving power system efficiency. A practical experimental setup is utilized to develop a working prototype, transforming 380 VDC to 48 VDC with a power capacity of up to 500 W. The setup incorporates dSPACE CP1103 to execute Model in the Loop (MIL), Software in the Loop (SIL), and Hardware in the Loop (HIL) methodologies. Additionally, it employs advanced control strategies such as passivity-based control (PCB) and canonical forms, which are compared with classical Proportional-Integral-Derivative (PID) control arrangements to propose a comprehensive control scheme that ensures stability in the presence of real-time disturbances (RT). Finally, a performance analysis is conducted, assessing important indicators like reaction time, precision of signals, stability of the system, and efficiency in resource utilization. The document concludes by offering a performance evaluation that encompasses PI, Cp, CpK, Z-score, and ITAE. This assessment considers factors such as response time, signal accuracy, system stability, and the efficiency of resource utilization.

In this paper a Fractional PID Control is presented. This control was designed for a hydropower plant with six generation units working in an alternation scheme. The parameters and other features of such a set of hydrogeneration units have been used to perform the respective tuning up. In order to assess the behavior of this controlled system, a model of such nonlinear plant is regulated through a classical PID by classical linearization of its set points, and then a pseudo‐derivative part is substituted into a Fractional PID. Both groups of signals contain variations of voltage suggesting some abrupt changes in the supply of electricity fed to the network. Both sets of resulting signals are compared; the simulations show that the Fractional PID has a faster response with respect to those plots obtained from the classical PID used.

This paper addresses an attitude tracking control design applied to multirotor unmanned aerial vehicles (UAVs) based on an ADRC approach. The proposed technique groups the endogenous and exogenous disturbances into a total disturbance, and then this is estimated online via an extended state observer (ESO). Further, a quaternion-based feedback is developed, which is assisted by a feedforward term obtained via the ESO to relieve the total disturbance actively. The control law is bounded; consequently, it takes into account the maximum capabilities of the actuators to reject the disturbances. The stability is analyzed in the ISS framework, guaranteeing that the closed loop (controller-ESO-UAV) is robustly stable. The simulation results allow validation of the theoretical features.

This document introduces a rapid control prototyping (RCP) approach applied to the industrial sector using a non-linear Quadratic Buck Converter (QBC) DC-DC. The goal is to reduce manufacturing costs for materials and electronic devices while enhancing the power quality in the system’s response. An experimental setup is utilized to create a functional model, converting 380 VDC to 48 VDC at a power level of 500 W. dSPACE CP1103 is employed to implement Model in the Loop (MIL), Software in the Loop (SIL), and Hardware in the Loop (HIL) simulations. Modern control techniques, including sliding mode control (SMC) and passivity-based control (PBC), are employed to devise a robust control scheme capable of maintaining stability in real-time (RT) and resisting disturbances. The document concludes with a performance analysis, PI, Cp, CpK, Z-score, and ITAE considering response time, signal accuracy, system stability, and resource utilization efficiency.