No abstract

Human–robot interaction is inherently available and used actively in ankle rehabilitation robots. This interaction causes disturbances to be counteracted on the rehabilitation robots in order to reduce the side effects. This paper presents a fractional order proportional–integral–derivative controller to improve the trajectory tracking ability of a developed 2-degree of freedom parallel ankle rehabilitation robot subject to external disturbances. The parameters of the controller are optimally tuned by using both the cuckoo search algorithm and the particle swarm optimization algorithm. A traditional proportional–integral–derivative controller, which is also tuned using both of the algorithms, is designed to test the performance of the fractional order proportional–integral–derivative controller. The experimental results show that the optimally tuned FOPID controller improves the tracking performance of the ankle rehabilitation robot subject to external disturbances significantly and decreases the steady-state tracking errors compared to the optimally tuned PID controller.

Load frequency control (LFC) is one of the essential process in interconnected power systems. To provide high quality, reliable and stable electrical power, designed controller should perform satisfactorily, i.e. suppress area frequency and tie-line power deviations. Within this scope, in this study, a high order differential feedback controller (HODFC) and a developed fractional high order differential feedback controller (FHODFC) are proposed for LFC problem in multi-area power systems for the first time. The gains of the HODFC and FHODFC are optimally tuned by particle swarm optimization (PSO) algorithm aiming to minimize integral of time weighted absolute error (ITAE) performance index. The superiority of the developed FHODFC are verified by comparing reported controller structures in the recent stateof-the-art literature and HODFC for two identical non-reheat thermal power system and two-area multisource power system consisting of gas, thermal and hydro generation units with/without consideration of HVDC link. To test the robustness of the designed controllers, varying system parameters and loading conditions are investigated. The governor dead band (GDB) and generation rate constraint (GRC) limitations are also considered for the system under study to examine non-linearity handling success of the proposed controllers. Performance results indicate that the developed FHODFC provides better dynamic response and robustness than other published techniques under nonlinearities, random load pattern, and variations in system parameters and loading conditions. INDEX TERMS Load frequency control, governor dead band, generation rate constraint, random load pattern, fractional calculus, fractional high order differential feedback controller, particle swarm optimization, robustness and transient response analysis.

No abstract

No abstract

No abstract

In this study, an antenna azimuth position control system is controlled by using a Proportional-IntegralDerivative (PID) controller and a fuzzy logic controller (FLC) designed in Matlab/Simulink environment. In order to obtain the best system response with FLC, different types of fuzzy rules and membership functions are tested. System responses with proposed controller and PID controller are compared to each other and commented according to these results.

Solar energy, which is one of the renewable energy sources, has an important role in meeting the increasing electrical energy demand of our globe. In recent years, many countries have established their energy policies based on solar energy, and researchers have been working on solar panel efficiency, maximum energy extraction from the sun, control and power electronics. The energy extracting from the sun is converted into electrical energy via solar panels. To extract continuously maximum energy level from the sun reduces installation costs and makes it easier to meet the demanded peak electrical power. Physical conditions such as muddy rain, snow and dusting place between the solar panel and the sun. This situation results the reduced electrical power extraction level which can be technically produced with clean solar panel surface. Therefore, it is also very important to keep the solar panels clean as well as the maximum power point tracking devices. In this study, a solar panel cleaning robot (SPCR) has been designed and tested in real time. The designed dual-motor and crawler robot moves horizontally and the cleaning brush runs on the vertical axis. In addition, the length of the solar panel array can be detected by position switches to keep the SPCR in desired working area.