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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.

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System modelling and simulation are essential in engineering especially in automatic control systems (ACS) engineering. At many universities, undergraduate curricula include systems and control courses with dynamic modelling and simulations in their syllabi. In order to design a controller for a physical system, one has to know the operational behaviors of that system very well so that a proper controller could be designed. Keeping this in mind, educational computer-aided software with a user-friendly visual interface was developed. The software provides an opportunity for students to simulate physical systems without and with the controllers they designed. Since it was developed to accompany undergraduate control system courses, the main purpose of this software was to create an interactive, practical, visual, and functional environment for the students who taking ACS courses. Therefore, it was called as virtual control laboratory (VCL). Basically, the students were able to design and simulate classical proportional-integral-derivative (PID) controllers and fuzzy logic controller (FLC). Besides, any other type of compensator with a transfer function or a state space model can be also combined with the physical system model for simulation and analysis. A laboratory type scope with two input channels was embedded in VCL in order to visually see and analyze the simulation results in the time domain. Responses from the students taking ACS course were also given to evaluate the proposed educational software from students' point of view. ß 2015 Wiley Periodicals, Inc. Comput Appl Eng Educ 24:122-130, 2016; View this article online at wileyonlinelibrary.com/ journal/cae;

This article is focused on increasing the tracking performance of a developed ankle rehabilitation robot subject to external disturbance. A plug-in-type repetitive controller cascaded to a proportional-integral-derivative controller is designed and implemented in order to make improvement in the tracking ability of the parallel mechanism while performing the common range of motion exercises which are intensive training exercises in ankle rehabilitation. First, the trajectory tracking control is simply implemented by the PID controllers, the parameters of which are optimally tuned using Cuckoo search algorithm. Then, the designed RC is plugged into the system and trajectory tracking control is carried out. Performance measurements of the PID controller and plug-in RC controller are estimated using error-based performance methods and considerable improvements are observed in attenuating the external disturbance and decreasing the tracking error when the plug-in RC is implemented.

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