The precise positional controls of piezoelectric actuators (PEA) are problematic due to highly-nonlinear hysteresis behavior which is inherent in piezoelectric materials. In existing PEA positional control applications that are based only on neural networks, the obtained control response results are insufficient for practical usage. In this paper we apply a combined approach by using a feedforward neural network (FNN) jointly with a BAT search algorithm in order to improve the positional control of an X-PEA mechanism model by also taking into account the hysteresis behavior. The proposed positional controller was successfully implemented and it was capable of significantly improving the overall control response result of an X-PEA mechanism model by minimizing the overshoot value and steady-state error, and decreasing the settling time. In addition, the BAT search algorithm can also be used for training the FNN, optimizing the FNN topology and reducing the computational complexity. The presented simulation results confirmed that the proposed positional controller with combined approach provides better results compared to the classical FNN control approach.
COBISS.SI-ID: 18662422
This article presents a modified robust disturbance observer-RIC for a mechanical-positioning system. The proposed RIC structure ensures a higher level of stability margin and offers transparent selection of the controller’s structure and feedback dynamic. The modified RIC controller design is divided into two main stages, where the first stage provides a design for the internal robust controller and the second a design for the external performance controller. The controller structure ensures a robust stability and performances property and good capability of low-frequency input and output disturbances suppression. The controller synthesis based on a pole-placement technique using optimization of the robust criteria based on even polynomials, and positive conditions. The solution to the problem is based on a multi-criterion optimization algorithm with a fixed order controller structure.
COBISS.SI-ID: 18339862
This paper presents the synthesis of an optimal robust controller design using the polynomial pole placement technique and multi-criteria optimisation procedure via an evolutionary computation algorithm (ECG) – differential evolution (DE). The main idea of the design is to provide a reliable fixed-order robust controller structure and an efficient closed-loop performance with a preselected nominally characteristic polynomial. The multi-criteria objective functions have quasi-convex properties that significantly improve convergence and the regularity of the optimal/suboptimal solution. The fundamental aim of the proposed design is to optimise those quasi-convex functions with fixed closed-loop characteristic polynomials, the properties of which are unrelated and hard to present within formal algebraic frameworks. The objective functions are derived from different closed-loop criteria, such as robustness with metric H∞, time performance indexes, controller structures, stability properties etc. Finally, the design results from the example verify the efficiency of the controller design and also indicate broader possibilities for different optimisation criteria and control structures.
COBISS.SI-ID: 18589974
We propose a new compressed sensing MRI approach that uses the discrete nonseparable shearlet transform (DNST) as a sparsifying transform and the fast iterative soft thresholding algorithm (FISTA) for reconstruction. FISTA has a simple design and has shown good convergence behavior. The DNST transform has excellent localization properties within the space domain and excellent directional selectivity. We utilize the frequency representation of the DNST canonical dual filters to obtain a memory efficient modified FISTA based algorithm with a simple and efficient way of calculating the update, tuned to the non tight frame DNST transform. The proposed approach shows improved performance and similar execution time when compared with other state of the art reconstruction approaches.
COBISS.SI-ID: 18778390
Angle of Arrival (AoA) is one of few techniques in the localization of a wireless sensor network. With two measured angles and with known distance between anchor the position of unknown node can be obtained. This paper deals with our approach of AoA measurement using a combination of more omnidirectional antennas and on low-cost ZigBee modules which enable measurements of Received Strength Signal Indicator (RSSI). The used omnidirectional microstrip antenna has almost a symmetrical radiation pattern with sharp minimums along the x antenna axis. Therefore, an algorithm based on an approach where an angle of arrival is obtained along a direction where the measured RSSI is minimal. This paper presents on our approach proposed methods, algorithms and comparison of them.
COBISS.SI-ID: 19336214