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 explains the whole process of a system design for the remote control of a stepper motor via web server. For this purpose a hardware structure is fully designed and implemented. Two types of communications were used to operate with the stepper motor. The first is realized by serial RS-232 protocol and the second one uses TCP/IP protocol for remote control. The TCP/IP protocol provides communication between server and client computers. The proposed control system is connected to the server. The main objective of this paper was to obtain a precise control of velocity or number of steps of the stepper motor. Validity and effectiveness of the used algorithm were verified through both simulations and experiments.

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.

This paper presents an implementation of soft computing methodologies, like genetic algorithm and fuzzy logic, in identification and control of 2DOF nonlinear helicopter model (Humusoft CE 150). The genetic algorithm is proposed for identification of the physical structure of 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 elevation and azimuth fuzzy logic Mamdani type controllers design in a simulation mode. 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.

This paper deals with a design and implementation of an incubator temperature control system. This system is composed of the incubator, a PLC-based PID controller, HMI (human-machine interface), DC dimmer as actuator and an NTC temperature sensor. A mathematical model of the incubator system with appropriate sensor and drives is derived through identification process based on step responses. Its model is implemented in Simulink program package. The parameters of the PID controller have been adjusted by using a self-tuning toolbox under Matlab/Simulink. The whole control system is realized in both simulation and experimental modes. The robustness and effectiveness of the proposed control system are demonstrated through comparison of simulation and experimental results.

This paper demonstrates the effectiveness of a genetic algorithm in identification of the unknown parameters of a nonlinear 2DOF laboratory helicopter model. The mathematical model of physical structure of the helicopter has fourteen unknown parameters which are necessary to be identified. For identification of this model a genetic algorithm is chosen because it enables finding referent results using less number of the experiments in comparison with other identification techniques. After the identification process has been carried out, the unknown parameters are determined and validated through comparisons of the simulation model response and response of the real helicopter system.

Abstract This paper describes how LEGO kits can be used to teach design and building of the complex robot system composed of the mobile robot platform and the robot arm. Both parts of proposed system are equipped with appropriate microcontrollers, sensors and actuators. All mechanical and electrical components are parts of Lego NXT Mindstroms™ Educational Robotic Kit. The control and communication software supports were building using Java programming language. This system could be controlled in two different modes, direct and Bluetooth controls. The effectiveness of the proposed complex system is demonstrated through several experiments, which provide an innovative use of the LEGO kits in robotics courses.

The purpose of this paper is to analyse and implement PI control for the permanent magnet DC motor. The control algorithm is realised using Siemens S7-200 programmable logic controller (PLC). The complex motor system is composed of DC motor, driver and tachogenerator. The main objective is to achieve a satisfactory time response of the system output under disturbances like death zone, nonlinearity, measurement noise and external load acting. The PI controller is designed in the programming environment on a previously identified nonlinear motor system. Then the PI controller is embedded into the S7-200 PLC. The effectiveness of this controller are tested in both simulation mode and experiments.

Market based approach (MBA) provides communication and coordination for robots in a virtual economy in which they can exchange tasks and resources for payment. Furthermore, trades are enabled via market mechanisms such as auction protocols in which an auctioneer is able to determine the robots best capable of achieving the tasks being offered. In this paper we purpose a modification of MBA for task allocation. This approach consists of auction announcement, bid valuation and submission and winner determination. Several scenarios where robots need to visit particular locations with time and range of wireless network constraints are used for approach verification. Additionally, the results obtained by this approach are compared with results from approach in Control and Coordination of Mobile Motes (CCMM).

In this paper we proposed the new concept which significantly decreases the development and implementation costs of standard SCADA systems. This system, as any other SCADA system, consists of MTU and RTU. This new concept is designated as PtP SCADA or PC-to-PC SCADA. The main approach to achieve several benefits is based on the idea to place standard PC configuration on both MTU and RTU sides of communication link in SCADA system. Unlike standard SCADA systems which, in majority of cases, have PLC as RTU, PtP SCADA systems have PC based RTU with custom software. PC based RTU is in charge of communication with MTU, direct control of the object, optional indirect control of the object over simple PLC's, storing data, and eventually independent decision making in mission critical situations. The main advantages of using PtP SCADA are lower development and maintenance costs, significant decrease of design and implementation complexity, market competitiveness with highly sophisticated SCADA systems. Main contribution of this concept to global SCADA concept is allowing the introduction of artificial intelligence on RTU side which is given as a guideline for further development. Although in this work we introduced the modified spiral model as new concept of design and development of PtP SCADA systems, the main focus of this work is not on modification of spiral modeling, but rather on new architectural and conceptual organization of SCADA systems.

This paper presents a design of the fuzzy logic control for a permanent magnet DC motor. The main objective is to achieve a robust controller under disturbances and unmodeled dynamics acting, such as load torque, dead zone, measurement noise and nonlinearities. The whole system contains the DC motor, driver, tachogenerator, external load and microprocessor based system (dSPACE CLP1004). This system is considered such as black box. The fuzzy controller is designed in simulation mode first. The model of whole system was obtained through identification procedure. Then this fuzzy controller is included into a real physical control structure. Control performance of the fuzzy controller in both simulation and experimental modes are compared under mentioned constraints. Also, results obtained by the fuzzy controller are compared with the same obtained by PID controller.