ABSTRACT
Control is a problem of finding a suitable (control) input driving a given system to a desired behavior. In general, there is extensive literature introducing the field of control and providing background material on solving control problems [1–3]. Having a system displaying a desired behavior is usually achieved by designing a controller that produces the necessary control in terms of the fed back actual (plant) output and a reference signal representing the desired (plant) output. The design of a controller working well for a given real plant in an actual environment requires the consideration of the behavior of the actual plant under the actual operating conditions [4–11]. In one extreme, such a controller design problem can be attempted to be solved by examining the simulated controller on a simulated plant under simulated operating conditions [2,12], while in another extreme, the approach relies on testing and tuning the controller hardware on the physical plant in the actual environment [13,14]. Testing the proposed controllers’ performance on the simulated or physical plant is followed by a redesigning or parameter tuning process performed offline or online. Both approaches have their own advantages/disadvantages and also difficulties for experimentation. For most of the cases, examining the controller candidates directly on the physical plant may not be possible in the laboratory environment or may be dangerous because of possible damages that may result [15,16]. In between these extremes lies an approach that mimics the physical plant in real time and in actual environmental conditions, especially in combination with the analog/ digital interface units. However, such an approach is not only complicated in software simulations but it also yields, with great probability, unreliable simulators that are highly sensitive to the unavoidable modeling errors that each simulated unit embodies [17,18].
