Classical Control System Research Articles

INTELLIGENT CONTROL OF ELECTRICAL DRIVE SYSTEM USED FOR ELECTRIC VEHICLES

Abstract An electric vehicle (EV) uses an electric motor for traction and chemical batteries, superconductors, combustion cells and / or inertial masses as energy sources. To avoid problems regarding the accuracy of the mathematical model of the system, the use of artificial intelligence in electric drives is a viable alternative. Among other advantages of using artificial intelligence in the electric drive system, it can be emphasized that its application reduces the design time and leads to avoiding problems with the introduction of the mathematical model in the system control algorithm. This paper presents several case studies of electrical vehicles and some considerations about intelligent control of EVs. Finally some experimental results that compare classical control system with fuzzy logic control system for EV are presented.

Retracted: Robot advanced intelligent control developed through versatile intelligent portable platform

The paper presents a versatile, intelligent portable robot platform VIPRo, which involves developing intelligent control interfaces by applying advanced control techniques adapted to the robot environment such Robot Neutrosophic Control (RNC), Robot Extenics Control (eHFPC), Robot Haptic Control (RHC), human adaptive mechatronics, implemented by high speed processing IT&C techniques and real time communication for a high amount processing data. An original virtual projection method is applied to SMOOTH firefighting robots through representation of the intelligent mobile robots in a 3D virtual environment using VIP-F2Ro with robotic strong simulator, an open architecture system and adaptive networks over the classical control system of the robot.

On integration of feedback control and safety systems: Analyzing two chemical process applications

This work focuses on two case studies and attempts to elucidate the dynamic interaction between feedback control and safety systems in the context of both model-based and classical control systems. In the first case study, the interaction of a model predictive control (MPC) system with a safety system is studied in the context of the methyl isocyanate (MIC) hydrolysis reaction in a continuous stirred tank reactor (CSTR) to avoid thermal runaway. We develop a specific action for the MPC to take when the safety system is activated due to significant feed disturbances that lead to thermal runaway conditions. In the second case study, we focus on a high-pressure flash drum separator for which the temperature, level, and pressure can be regulated using proportional-integral (PI) controllers. Using a large-scale dynamic process simulator, we demonstrate that modifying the tuning parameters of one of these PI controllers based on the safety system being on or off leads to improved closed-loop performance compared to the case in which the tuning parameters of the PI controller remain the same regardless of the state of the safety system.

Evaluation of classical reinforcement and passive control systems on a reinforced concrete bridge subjected to seismic loading

Evaluation of classical reinforcement and passive control systems on a reinforced concrete bridge subjected to seismic loading

Evaluation of classical reinforcement and passive control systems on a reinforced concrete bridge subjected to seismic loading

In this paper, different strategies are studied with the main objective to reduce structural demand and damage of an existent bridge in Mendoza, Argentina, with post-tensioning reinforced concrete girders that are a common structural typology in the region. A numerical study was carried out with this purpose. The numerical model was calibrated against experimental measurements of vibration natural frequencies. The alternatives studied are: a) classical reinforcement of the structural overall stiffness; b) tuned mass dampers; c) viscous dampers; d) metallic dampers. The model is subjected to real near-fault seismic records, thereby obtaining response parameters to evaluate the efficiency of each protective system. The response is evaluated not only in terms of reduction of displacements, but also in increasing of shear force in key elements, which is a negative characteristic of some of the systems studied. Advantages and disadvantages of each studied system are highlighted.

Finite state machine control for aircraft electrical distribution system

This study deals with the development of new control logic for more electric aircraft (MEA) electrical power systems (EPSs). A key aspect of the MEA concept is that traditional pneumatic and hydraulic loads are replaced by electrical equivalents. These new electrical systems are more reliable, highly efficient, and easier to replace or maintain. However, as the number of on-board electrical loads increases the electrical distribution systems on-board are becoming more and more complex. As a result, the control system needs to be adapted and improved in order to allow better manage the overall electrical energy flow, provide faster computational operations, and ensure operation of safety-critical loads under all fault scenarios. This study first gives a brief analysis of the different electrical system topologies before outlining potential control strategies which may be applicable to future MEA EPSs. A new control concept for MEA EPSs is then investigated and considered as a potential substitute of the classical control systems. Finally, a model of the newly proposed logic is implemented and simulated showing how it is able to select and apply a correct reconfiguration of the electrical system under different operating conditions.

Simulation Model of Wind Turbine Power Control System with Fuzzy Regulation by Mamdani and Larsen Algorithms

Abstract 
 The aim of this work is to create a power control system for wind turbines based on fuzzy logic. Three power control loop was considered including: changing the pitch angle of the blade, changing the length of the blade and turning the nacelle. The stochastic law was given for changes and instant inaccurate assessment of wind conditions changes. Two different algorithms were used for fuzzy inference in the control loop, the Mamdani and Larsen algorithms. These two different algorithms are materialized and developed in this study in Matlab-Fuzzy logic toolbox which has been practically implemented using necessary intelligent control system in electrical engineering and renewable energy concepts.
 A comparison was done to access the functionality of the developed power control system of fuzzy logic and classical control system with PID – control. It can be concluded that the power control system of fuzzy logic allows to accurately maintain production under the control target function for each work area. When switching operation of wind turbines, it has the distinction that from 13.5 m/s to another wind velocity value, there is no overshoot and a typical of classical control systems, and when the wind velocity V is less than13.5 m / s, the pitch angle of the blades should be slightly greater than zero, and if it has increased by 5 °, then blade length should be minimal as possible. Simulation program proved the possibility of effective power regulation for the large wind turbines controller fuzzy type on the basis of knowledge production "if - then" rules, which were shown to be effective on these wind turbines control.
 Keywords: Mamdani and Larsen algorithms fuzzy inference, Matlab Fuzzy Logic ,Fuzzy-PID controllers, Wind turbine.

Optimal regulation problem with fractional order performance index

This paper addresses a new view to the optimal control problems in a more realistic perspective. It is clear for control engineers that one of the most serious adversities in defining the performance index is to decide what characteristics of the system response are important to be considered and how they have to be weighted if they are not treated totally equal. In this manuscript, using fractional order integration, a time-weighted performance index is introduced for evaluating the performance of optimal regulation problems which extends the quadratic cost functional in the classical process control systems. Such formulations are gained in the light of intrinsic kernel in the definition of the Riemann–Liouville fractional order integral which weighs the Lagrangian of the performance index upon the time progresses. Moreover, a constraint on the fractional order derivative of the control signal is included in the generalized performance index to overcome the saturation problem occurred in the real control systems. The proposed techniques are supported by some discussions and several numerical simulations.

Event-Based Sensing and Control for Remote Robot Guidance: An Experimental Case.

This paper describes the theoretical and practical foundations for remote control of a mobile robot for nonlinear trajectory tracking using an external localisation sensor. It constitutes a classical networked control system, whereby event-based techniques for both control and state estimation contribute to efficient use of communications and reduce sensor activity. Measurement requests are dictated by an event-based state estimator by setting an upper bound to the estimation error covariance matrix. The rest of the time, state prediction is carried out with the Unscented transformation. This prediction method makes it possible to select the appropriate instants at which to perform actuations on the robot so that guidance performance does not degrade below a certain threshold. Ultimately, we obtained a combined event-based control and estimation solution that drastically reduces communication accesses. The magnitude of this reduction is set according to the tracking error margin of a P3-DX robot following a nonlinear trajectory, remotely controlled with a mini PC and whose pose is detected by a camera sensor.

On the Relation Between the Minimum Principle and Dynamic Programming for Classical and Hybrid Control Systems

Hybrid optimal control problems are studied for a general class of hybrid systems where autonomous and controlled state jumps are allowed at the switching instants and in addition to terminal and running costs switching between discrete states incurs costs. The statements of the Hybrid Minimum Principle and Hybrid Dynamic Programming are presented in this framework and it is shown that under certain assumptions the adjoint process in the Hybrid Minimum Principle and the gradient of the value function in Hybrid Dynamic Programming are governed by the same set of differential equations and have the same boundary conditions and hence are almost everywhere identical to each other along optimal trajectories. Analytic examples are provided to illustrate the results and, in particular, a Riccati formalism for linear quadratic hybrid tracking problems is presented.

Stochastic Multi-Objectives Supply Chain Optimization with Forecasting Partial Backordering Rate: A Novel Hybrid Method of Meta Goal Programming and Evolutionary Algorithms

This study proposes a model for a multi-objective, multi-buyer, multi-vendor, multi-product and multi-constraint supply chain. The buyers’ demand rates are stochastic variables with known probability distribution functions. The classical ([Formula: see text]) inventory control system is used to manage the inventories of all buyers where the lead times are production rate dependent. Shortage is permitted and is partially backordered where the partial back ordering rate is forecasted. The model is considered as a multi-objective integer nonlinear programming problem including cost, service level and lead time objectives and using a novel hybrid method, a hybrid of Meta Goal Programming (MGP) and Firefly Algorithm (FA) are solved. Numerical examples are given to illustrate the proposed method in the study. The results of the study are compared to other hybrid methods of Meta Goal Programming with other evolutionary algorithms such as Bees Algorithms (BA), Particle Swarm Optimization (PSO), Genetic Algorithm (GA) and Simulated Annealing (SA).

Gas Phase Train in Upstream Oil & Gas Fields: PART-III Control System Design

This paper presents and implements a control structure solution based on MPC for two control problems affecting gas phase train in the existing oil and gas production plants: The disturbance growth in the series connected process and the control system dependency on operators. This work examines the integration of small size MPC’s with the classical PID control system to handle interactive control loops in three series gas treatment processes.

LabVIEW-based Classic, Fuzzy and Neural Controllers Algorithm Design Applied to a Level Control Prototype

This work presents the algorithm design of classic control, fuzzy control and neural control applied to a level control prototype. Classic control systems use PI and PID control actions; in order to tune such actions, Ziegler and Nichols oscillating method was used. It was designed a proportional, derivative and incremental fuzzy control system. As well, an inverse mode neural controller and an intern model neural controller are presented. As a first stage, simulation results were obtained using Matlab. Afterwards, an experimental implementation for each controller was carried out using LabVIEW based virtual instruments; a comparison between the functionalities of the presented controllers is done. Finally, the neural control system was implemented in an FPGA and the performance was compared to the one implemented in the LabVIEW virtual instruments.

Energy saving in operations management through variable-speed drive technology: environmental versus economic convenience

CO2 emissions are mainly due to electricity generation. The percentage of electrical energy used within industry rises up to 70% in industrialised countries and electrical motors use the greatest part. Due to the high degree of flexibility required in production systems, the classical on-off control system causes large energy losses due to mismatches between the output power of fixed-speed motors and the mechanical power demands of the electromechanical system. Variable-speed drive (VSD) systems, developed through the inverter-fed alternating current technology, are identified as the motor system technology with the most significant energy-saving potential. The purpose of this paper is to analyse and compare both the economic and the environmental benefits related to the potential retrofitting of existing production systems managed using the traditional on-off control according to different variable typologies: the flexibility requirement variables, the production system variables and the variables related to the specific country considered. As a result, the paper identifies the relation between the two economic and environmental objectives according to the analysed variables. Two company cases are reported in order to demonstrate both the economic and the environmental benefits of applying the VSD technology to existing production systems.

Optimal Threshold Setting for Event-Based Control Strategies

In this paper, an event-based control strategy for mobile robots is proposed. The solution includes new features that minimize the effects of the noise on the system. Two methodologies have been developed to compensate the perturbations. To avoid the effects of such perturbations, a threshold calculator and a perturbation estimator are included in the system. The proposed system is compared with classical control systems based on discrete time. Different scenarios are analyzed in the experiments to check its performance. The stability and the improvements of the proposed control strategy are also analyzed in the experimental results.

Análisis y reflexiones sobre el control de constitucionalidad de las leyes

The author makes a descriptive analysis from the historical perspective of systems known as classic control systems for constitutionality of laws (American and European), addressing their main characteristics and impact on each region. The author then analyzes the characteristics of each model, describing the tools that, at his judgment, constitute integrating elements of the new constitutionality control models.

프로그램 기반의 시간응답 해석에 의한 고전제어 시스템 이해

프로그램 기반의 시간응답 해석에 의한 고전제어 시스템 이해

ENGLISH

In this study, dynamic behaviour modelling of AdA±guzel hydroelectric power plant (HEPP) is executed by implementing Matlab/Simulink software program to carry out the short circuit analysis in case of various charging of electricity loads. By building a system to reflect the behaviour of real feature under the control of the governor and using both classic (PID) and self-adjustable fuzzy logic control system (FLC) performances of 36MVA powered synchronous generator and dynamic model of the other components in the system were studied in case of short circuit faults of the possible phase-earth, phase-phase, two phase and three phase earth. It is observed that in the simulation studies which were carried out the fuzzy logic control system became stable in a short period of time, within the limits of allowed tolerance when both control systems compared.

Design and Development of Computational Intelligence for Enhanced Adaptive Cruise Control Using Arduino

In today’s fast paced world, transportation plays a very important role. Of all the different types of transportation available, cars are one of the most common and most preferred means of transportation for the majority of people. The classical Cruise control System maintains the pre-set speed and will also adapt itself to the change in acceleration of the preceding vehicle. But it is not sophisticated enough and reduces its speed to zero in case of critical conditions. In the proposed system, in addition to obstacle detection, a new feature is added which enables the vehicle to switchover to an empty lane when the preceding vehicle is too near or whenever there is a possibility of crash. This paper discusses about the implementation of the same. The main input to the system is the data collected by the ultrasonic sensors fixed to the four sides of the vehicle. The main processing unit analyses the data collected and sends out a control signal to the motor driver in accordance with the algorithm. H-Bridge in this system controls the speed and the direction of the vehicle by giving the appropriate control signal to the motor connected to the wheels. This paper deals with the design of the prototype model of the proposed system. The main control part of our system is realised by the Arduino microcontroller.

Fractional order PID and application of its circuit model

In this paper, the circuit design of a fractional order proportional-integrated derivation (FO-PID) controller for synchronization between different FO chaotic systems has been described. Chaotic synchronization and control are used in different applications in nonlinear physical systems such as performance tests for controllers and chaotic communication systems. FO chaotic systems have been created, and the synchronization control of these two systems has been carried out using an FO-PID controller. The total square error should be minimized in order to determine the parameters and orders of the designed FO controller circuit. The results obtained using the FO controller are better than those obtained using classical control systems. Using an FO-PID controller, the time to reach synchronization decreased significantly.