This paper deals with measuring and reduction of odometry errors of a differential-drive mobile robot. For this purpose an algorithm for reducing systematic odometry errors caused by uncertainty of an effective wheelbase and unequal wheel diameters is proposed. The algorithm calculates three calibration coefficients using an optimization based on Levenberg-Marquardt algorithm. These coefficients compensate the effects of unknown values of wheel radius and unknown value of the wheelbase. The mobile robot location during a motion is determined based on visual system measurements. For evaluating the proposed algorithm three different tests are considered: straight line experiment, turn in place experiments, unidirectional square path experiment. Simulation and experimental results demonstrate the effectiveness of the proposed algorithm in reducing the systematic odometry errors.

The paper exploits advantages of the genetic algorithm and fuzzy logic in identification and control of 2DOF nonlinear helicopter model. The genetic algorithm is proposed for identification of the helicopter system, which contains a helicopter body, main and tail motors and drivers. The quality of helicopter model achieved was validated through simulation and experimental modes. Then, this model is used to design of elevation and azimuth Mamdani type fuzzy controllers. The main objective of the paper is to obtain robust and stable controls for wide range of azimuth and elevation angles changing during the long time flight. The robustness and effectiveness of both fuzzy controllers were verified through both simulations and experiments. Also, a comparative analysis of proposed fuzzy and traditional PID controllers is performed.

Remote control is one of the best solutions for managing inaccessible systems. Many researches have been made in the field of the remote control [1-4]. These researches have improved certain aspects of industry, medicine, military, etc. The benefits of remote control are numerous such as: operating in hazard environment, telemedicine, missile guidance, etc. The most important characteristic of remote control is operating in real-time as shown in papers form references [5-7].

This paper proposes an approach of digital controller design on microcontrollers based on control surface disretization. As experimental setup a simple system composed of a DC motor, the PWM drive and a encoder was built. Identification of this simple system was done using the first order linear model and the Hammerstein-Wiener model. The quality of these models was compared based on the fitness function and their ability to cope with system nonlinearities. A discrete PI speed controller was designed based on the Hammerstein-Wiener model and tuned by the Gauss-Newton optimization algorithm. The Fuzzy logic controller was designed on the basis of the PI controller behaviour with genetic algorithm parameter tuning. The control surface of the Fuzzy logic controller was discretized for microcontroller implementation. Both controllers were implemented on the Arduino Mega platform and their control performances were tested and compared.

This work considers the whole process of making a path finding simulator for Pioneer 3DX mobile robot. This simulator needs to be provided implementation of various optimal path finding algorithms and make their comparisons. For this purpose a software solution (GUI in Matlab) has been designed and tested. The simulator allows selecting mazes, different starting and finishing nodes and algorithms. Five different algorithms were used to determine the shortest path between nodes for a mobile robot within various mazes: Breadth-first search, Depth-first search, Bellman-Ford algorithm, Dijkstra's algorithm and A∗ algorithm. The main objective of this paper was to obtain fully and precise information on routing and finding the shortest path between two nodes within a maze for the mobile robot. Validity and effectiveness of the used algorithms were verified through both simulations and experiments.

Different methods for position control of a DC servomotor are examined. Position is measured with a low-resolution incremental encoder that is a cheap solution that allows for free movement of motor shaft. This kind of measurement affects control and degrades its performance. Entire system is first identified using Matlab System Identification Toolbox. P and PD controllers, along with cascaded and observer-based controllers are synthesised and tested. Sugeno type fuzzy controller with two inputs and constant output membership functions shows the best results of the tested controllers in both simulation and testing done on a real system. Simulation is performed with Matlab Simulink. Control system prototyping is done using DS1104 board.

This paper deals with a design and implementation of a remote position control system for a mobile robot. The system is composed of the mobile robot (controlled object), PC as positioning controller, camera as sensor and ZigBee based wireless communication device. The camera captures images of the mobile robot. Developed image processing algorithms (Matlab platform) determine the robot's position and orientation. Based on this data the implemented system controls the robot's position. Control signals are sent via modules for wireless communication. The whole control system is realized and experimental results have been obtained. The experimental results confirm the robustness and effectiveness of the proposed control system.

This paper presents the control of induction motor via PROFINET network including a remote control using the OPC (OLE for Process Control) standard. This system is composed of induction motor, encoder, frequency converter, PLC (Programmable Logic Controller) and two PCs (server and client). The motor control is PLC based with PID (Proportional-Integral-Derivative) controller, while PCs are used as HMI (Human Machine Interface) devices for controlling and supervising the plant. PC which represents OPC server is connected with PLC via Ethernet network, while connection between frequency converter and PLC is established via PROFIBUS DP protocol. Two PCs are connected using OPC standard, where physical connection between them is achieved using LAN (Local Area Network). The obtained experimental results demonstrate a possibility to establish local and remote control over our system while ensuring system's stability and efficiency.

In this paper both hardware and software systems for GPRS communication and GPS navigation are developed. The hardware structure of GPS navigation module was build using Cinterion XT65 platform and appropriate electronic components. The overall navigation system is client-server based that uses GPS and GPRS communications. The GPS communication is used between client (mobile robot) and satellites, while GPRS communication connects server (PC) and client. The algorithm for mobile robot position estimation exploits a triangulation technique. Multiple algorithms (including a fuzzy regulator) for avoiding obstacles are implemented in order to provide safe and precise movement towards the destination point given to robot. The effectiveness and quality of proposed hardware and software structures are verified by experiments.

This paper explains the whole process of making a system for remote control of a robot arm with five degrees of freedom (DOF). For this purpose a hardware structure was fully designed and implemented. The hardware structure is based on microcontroller PIC16F877A and surrounding architecture that controls movement of different axis of the arm. The arm has no sensors, so the visual information from the camera was used as feedback. Two communications were used to operate robot arm. The first one is realized by serial RS-232 protocol between PC and Microcontroller, and this communication is used to operate the arm. The second communication uses TCP/IP protocol for remote control. The TCP/IP protocol provides communication between server and client computers and sends information of position of robot arm. For interaction with user appropriate GUI is implemented in MATLAB. The main objective of this paper was to obtain fully and precise control of every degree of freedom.

This paper describes indoor temperature regulation. Indoor environment temperature regulation is most frequent type of regulation. To achieve this goal a small scale model was built with software support as well. This system model is composed of the incubator, DC controlled dimmer, ME — RedLab data acquisition module as AD/DA converter, a Matlab-based controller, GUI (Graphical User Interface), and an NTC temperature sensor. System identification using step response was carried out to determine a mathematical model of the system which was implemented in Simulink program package. Within the Simulink model P, PI, PID and fuzzy controller were designed. Results acquired during simulation were successfully applied on the real system. Both simulation and experimental results are consistent. It is shown that system developed on simulation level can be translated to the real system which simplifies the regulator design.

This paper deals with a simple procedure for map building as well as planning mobile robot trajectories. This approach divides the above problem into three stages: first, a design and construction of simple differential wheeled robot with ZigBee wireless communication; second, development of applications for mobile robot and PC which provide 2D map building of robot's environment using IR sensors; and third, development of applications for mobile robot and PC which provide trajectory planning and robot motion control for created maps. PC applications are implemented using Matlab GUI tool. Finally, this paper also shows developed wireless communication protocol for data exchange between mobile robot and PC. The robustness and effectiveness of the proposed system are demonstrated through experimental results.

This paper focuses on problems which arise from network controlled systems within master-slave type of Communications. Since the master and slave are connected over the network, network-induced time-varying delay has negative impact on system stability and control system performance. In order to compensate an influence of delay in NCS we proposed the improvement of two control strategies, Smith predictive and parallel fuzzy-PI controllers. Design of parallel fuzzy-PI controller has no demands for mathematical model of controlled system. Parameters of PI controller are adjusted adaptively depending on the delay. Adaptive Smith predictor is based on the adaptive loop that decreases influence of network-induced delay. It requires a mathematical model of the controlled system. Furthermore, simulations and practical experiments are given to illustrate the effectiveness and robustness of the proposed methods.

This paper presents a design of fuzzy logic control for 2DOF laboratory helicopter model (Humusoft CE 150) which represents a nonlinear and highly cross-coupled system. The controller is composed of two fuzzy logic controllers for azimuth and elevation controls. The main objective of the paper is to obtain robust and stable controls for wide range of azimuth and elevation angles changing during the long time flight. The quality and effectiveness of both fuzzy controllers were verified through both simulations and experiments. Also, a comparative analysis of proposed fuzzy and traditional PID controllers is performed.