INVERTED PENDULUM WITH LINEAR SYNCHRONOUS MOTOR SWING UP USING BOUNDARY VALUE PROBLEM

Research in the field of underactuated systems shows that control algorithms which take the natural dynamics of the system’s underactuated part into account are more energy-efficient than those utilizing fully-actuated systems. The purpose of this paper to apply the two-degrees-of-freedom (feedforward/feedback) control structure to design a swing-up manoeuver that involves tracking the desired trajectories so as to achieve and maintain the unstable equilibrium position of the pendulum on the cart system. The desired trajectories are obtained by solving the boundary value problem of the internal system dynamics, while the optimal state-feedback controller ensures that the desired trajectory is tracked with minimal deviations. The proposed algorithm is verified on the simulation model of the available laboratory model actuated by a linear synchronous motor, and the resulting program implementation is used to enhance the custom Simulink library Inverted Pendula Modeling and Control, developed by the authors of this paper

Návrh a experimentálne overenie algoritmu optimálneho riadenia pre výukový model mechanického systému

Článok sa zaoberá návrhom algoritmu optimálneho riadenia podľa kvadratického kritéria s využitím sumátora a jeho aplikáciou na riadenie simulačného/reálneho laboratórneho modelu – helikoptéra s cieľom riešiť problém sledovania zmien referenčných hodnôt riadiacej veličiny. Návrh modifikovaného algoritmu optimálneho riadenia so sumátorom vychádza zo znalosti stavového popisu modelu mechanického systému a je verifikovaný v riadiacej štruktúre naprogramovanej v simulačnom jazyku Matlab/Simulink s využitím S-funkcií. Vizualizácia získaných výsledkov je zrealizovaná pomocou vytvorených internetových aplikácií a technológie Matlab Web Server. Internetový prístup zjednodušuje verifikáciu navrhnutého algoritmu v simulačných schémach za účelom testovania jeho vlastností na riadenie simulačného nelineárneho a virtuálneho modelu helikoptéry. Článok sa zaoberá aj možnosťou aplikácie algoritmu optimálneho riadenia na nelineárny výukový model s využitím vstupno/výstupnej karty a funkcií Real Time Toolboxu na jej ovládanie

Application of results of experimental identification in control of laboratory helicopter model

This article deals with experimental identification and control of laboratory helicopter model CE 150 manufactured by company Humusoft. Structure of the identified system was approximated by linear black-box models. Discrete Input/Output Auto-Regressive Moving Average model with eXternal input (ARMAX) and its state space equivalent were used. Parameters of the models were estimated by regression techniques using System Identification Toolbox for Matlab. Acquired models were validated using simulations, residual analysis and real-time control. Input/output data necessary for identification were obtained by measurements from laboratory model and were processed using Real-Time Toolbox for Matlab. Based on acquired mathematical models input/output and state space controllers were designed (input/output pole placement with integration, state space pole placement with integration and observer). Designed controllers were implemented in Matlab environment using the Real Time Toolbox and their performance was verified by real-time control of the helicopter model

Design of Aerodynamic Ball Levitation Laboratory Plant

This paper presents the development of a new Aerodynamic Ball Levitation Laboratory Plant at the Center of Modern Control Techniques and Industrial Informatics (CMCT&II). The entire design process of the plant is described, including the component selection process, the physical construction of the plant, the design of a printed circuit board (PCB) powered by a microcontroller, and the implementation of its firmware. A parametric mathematical model of the laboratory plant is created, whose parameters are then estimated using a nonlinear least-squares method based on acquired experimental data. The Kalman filter and the optimal state-space feedback control are designed based on the obtained mathematical model. The designed controller is then validated using the physical plant

SENSORS FAULT DIAGNOSIS ALGORITHM DESIGN OF A HYDRAULIC SYSTEM

This article presents the sensors fault diagnosis system design for the hydraulic system, which is based on the group of the three fault estimation filters. These filters are used for estimation of the system states and sensors fault magnitude. Also, this article briefly stated the hydraulic system state control design with integrator, which is important assumption for the fault diagnosis system design. The sensors fault diagnosis system is implemented into the Matlab/Simulink environment and it is verified using the controlled hydraulic system simulation model. Verification of the designed fault diagnosis system is realized by series of experiments, which simulates sensors faults. The results of the experiments are briefly presented in the last part of this article

Návrh a experimentálne overenie algoritmu optimálneho riadenia pre výukový model mechanického systému

Článok sa zaoberá návrhom algoritmu optimálneho riadenia podľa kvadratického kritéria s využitím sumátora a jeho aplikáciou na riadenie simulačného/reálneho laboratórneho modelu – helikoptéra s cieľom riešiť problém sledovania zmien referenčných hodnôt riadiacej veličiny. Návrh modifikovaného algoritmu optimálneho riadenia so sumátorom vychádza zo znalosti stavového popisu modelu mechanického systému a je verifikovaný v riadiacej štruktúre naprogramovanej v simulačnom jazyku Matlab/Simulink s využitím S-funkcií. Vizualizácia získaných výsledkov je zrealizovaná pomocou vytvorených internetových aplikácií a technológie Matlab Web Server. Internetový prístup zjednodušuje verifikáciu navrhnutého algoritmu v simulačných schémach za účelom testovania jeho vlastností na riadenie simulačného nelineárneho a virtuálneho modelu helikoptéry. Článok sa zaoberá aj možnosťou aplikácie algoritmu optimálneho riadenia na nelineárny výukový model s využitím vstupno/výstupnej karty a funkcií Real Time Toolboxu na jej ovládanie

Riadenie laboratórneho modelu hydraulického systému

In this article a laboratory model of hydraulic system is presented with emphasis to mathematically-physical description of its dynamics and technical implementation, which makes possible to verify different algorithms for dynamical system identification and control. Two different approaches to laboratory model control in term of communication with control system are introduced. The article proceeds with the laboratory model of hydraulic system control by several control algorithms designed on the basis of linear approximation of physical system. Results of laboratory model control with classical digital PID and polynomial controllers are mentioned in the article. Optimal control algorithms are represented by linear quadratic control and its extended version with summator and also with two different predictive control algorithms.V článku je prezentovaný laboratórny model hydraulického systému z hľadiska matematicko-fyzikálneho opisu jeho dynamiky a technickej realizácie, ktorá umožňuje overovať rozličné algoritmy identifikácie a riadenia dynamických systémov. Uvedené sú dva rôzne prístupy k riadeniu laboratórneho modelu z pohľadu komunikácie s riadiacim členom. Článok sa zaoberá riadením laboratórneho modelu hydraulického systému pomocou niekoľkých algoritmov riadenia navrhnutých na základe lineárnej aproximácie fyzikálneho systému. V článku sú uvedené výsledky riadenia laboratórneho modelu pomocou klasických číslicových PID regulátorov a polynomiálneho regulátora, optimálne algoritmy riadenia zastupuje lineárne kvadratické riadenie a jeho rozšírená verzia so sumátorom a taktiež dva odlišné algoritmy prediktívneho riadenia

Application results identification based on genetic algorithm in nonlinear control design of magnetic levitation system

In this paper is presented the SISO laboratory model of Magnetic levitation in terms of mathematic description, which allows verifying the different approaches of identification and control. The nonlinear simulat ion model of the Magnetic levitation based on the mathemat ical model of the Magnetic levitation system is described. The unknown parameters of the Magnetic levitation model are identifying with using the genetic algorithm or direct measurement on the laboratory model and validation the obtained model parameters is performed after the identification. In this paper are also presented the control results of Magnetic levitation simulat ion and laboratory model with using the optimal state control with integrator method and the exact feedback linearizat ion input/output method