This work focuses on the design of driver for PiezoLegs actuator used for high precision positioning purposes. Motor is driven with the set of periodical voltages with known frequency, amplitude and phase shift between the phases. Motor's operation has been investigated in detail and clear relationships between the amplitude and phase shifts between the phases and motor step size have been established. According to the motor analysis, set of design requirements for the design of driver is given. Particular solution meeting these requirements and satisfying the given design constraints is presented. Driver is experimentally evaluated for power consumption and analyzed in frequency domain, it's performance is compared to the performance of a commercially available driver for the same motor. Designed driver shows improved performance.

This work focuses on the design of adaptive controller for high precision positioning purposes using PiezoLegs actuator. Actuator is driven with the set of periodical sine shaped voltages with known frequency, amplitude and phase shift between the phases. Clear relationships between the amplitude and phase shifts between the phases and actuator step size have been established. Based on these relationships adaptive controller has been designed. Controller is a linear, cascaded type of feedback controller that uses position feedback from an encoder. Based on the information of the absolute error controller performs the adaptive step size modulation by changing amplitude or phase shift of the driving voltages. Proposed algorithm is validated experimentally. Experimental results show satisfactory level performance, controller achieves fast settling time, no overshoot response and high accuracy of positioning with small steady state errors.

This paper describes the implementation of Takagi-Sugeno fuzzy controller that is based on PIC18F4680 microcontroller, made by Microchip company. The paper explains the whole realization procedure, from theoretical explanation to hardware and software solutions. Whole Takagi-Sugeno fuzzy reasoning procedure is adjusted so it can be implemented on a microcontroller that has limited memory resources. Also, execution speed is taken into account. Hardware and software part of the system are also described, especially the specific solutions that enable the controller to function properly. After the system has been realized, it has been validated experimentally, by recording the control surface of the controller, and its usage on the laboratory model for the control of liquid level in a reservoir was tested.

This paper engages the problem of adjusting the zero-order Sugeno fuzzy reasoning, so it could work on relatively simple and cheap microelectronic circuit, such as microcontoller. In this paper, a way to present the fuzzy system in a convinient form for storage in the microcontroller memory is shown. Also it was shown that the whole fuzzy reasoning can be reduced to operating exclusively on integer numbers.

Neural networks have been applied very successfully in the identification and control of nonlinear dynamic systems. The paper presents a design of neural network based control system for 2DOF nonlinear laboratory helicopter model (Humusoft CE 150). The main objective of this paper is to develop artificial neural networks to control helicopter's motors, or consequently elevation and azimuth angles. Neural networks are obtained by cloning various type of controllers designed in our previous papers. Those procedures included a cloning linear PID controller, gain scheduling controller and fuzzy controller.

The paper presents a design of 3D simulator for 2DOF laboratory helicopter model (Humusoft CE 150) and its practical implementation in various control system structures. The developed simulator provides testing performance of different control algorithms and visualization of results obtained. The 3D simulator has been designed and developed using the VRML programming language under the Virtual Reality toolbox in Matlab/Simulink. The effectiveness of this simulator are demonstrated during simulation and experiments on the 2DOF helicopter model using different control techniques, such as PID, adaptive gain scheduling and fuzzy controllers. Some of them have been designed in this paper.

The paper discusses the problems of design and implementation of three-dimensional simulator for control of laboratory model helicopter. The research is realized under student project at the Department of Automatic Control and Electronics of Faculty of Electrical Engineering in Sarajevo. For this purpose the HUMUSOFT CE150 laboratory helicopter model was used. In order to verify various control algorithms the 3D simulator is designed. Simulator was developed in Matlab/Simulink environment using the Virtual Reality Modelling Language (VRML). Three-dimensional helicopter was built by using 3D Studio Max script. The quality of this simulator is tested during the helicopter motion with PID controllers.

The paper describes a digital PID controller realized in the framework of a student project at the Department of Automatic Control and Electronics of Faculty of Electrical Engineering in Sarajevo. This project included the complete solution, from hardware design to software implementation of control algorithms.