Jan Ciganek

Advanced methods of controller design: Simulation and co-simulation on FPGA

The presented paper deals with design, co-simulation and comparison of three controller design methods (Internal Model Control, Pole-Placement, PID by Modulus Optimum) applied in the control of processes with complex dynamics. The presented and tested methods guarantee robust stability and high performance of controlled system. Proposed algorithms were successfully implemented in Matlab-Simulink using System Generator Toolbox and co-simulated on the Field Programmable Gate Array (FPGA) technology for the control of motor system model.

Advanced methods of controller design for pneumatic servodrives

A development of advanced control methods based on robustness, optimality and prediction is an important and challenging task. In recent years, a new control approaches have emerged to replace or augment conventional control engineering methods. The paper presents: design, verification and comparison of three advanced methods (IMC, MPC, PLM) applied in the control of dynamic processes with complex dynamics. In this paper three different methods were tested and applied to the position control of pneumatic servodrives. The presented and tested methods guarantee robust stability and high performance of the pneumatic servodrives control.

Advanced complex dynamics process control

In recent years, new control approaches have emerged to replace or augment conventional control engineering methods. The paper presents design, verification and comparison of two advanced methods (IMC, MPC) applied in the control of dynamic processes with complex dynamics. Development of advanced control methods based on robustness, optimality and prediction is an important and challenging task. The presented methods guarantee robust stability and high performance of manipulator control.

Fuzzy tracking controller for shape optimized robotic system

The paper deals with an effective approach of the robust controller design, based on the fuzzy logic. We developed algorithms with variable sampling for trajectorytracking. The proposed controller design and sampling algorithms are verified on the case study of the chosen mechatronic system. All numerical and graphical results are obtained in Co-simulation of combination two different modeling systems - Matlab-Simulink and MSC Adams. The paper shows the methodology of energy cost reduction using shape optimized model based on the system analysis made in system ANSYS.

Robust controller design based on reflection vectors

The paper deals with simple and robust discrete controller design using new approach using the reflection vectors techniques. We assume that the controller structure consists of feed-forward and feedback parts. Developed robust algorithms were tested on the case study examples for different dynamical processes stable, unstable and oscillating type. Simulations were realized in MATLAB-Simulink. Obtained numerical and simulation results confirm applicability of the theoretical principles for robust control of processes subject to parametric model uncertainty.