2016 (vol. 26) - Number 4
Practical and asymptotic stability of fractional discrete-time scalar systems described by a new model
D. Krokavec, A. Filasova, P. Liscinsky:
On fault tolerant control structures incorporating fault estimation
Hyperchaos, adaptive control and synchronization of a novel 4-D hyperchaotic system with two quadratic nonlinearities
H. Górecki, M. Zaczyk:
Analytic solutions of transcendental equations with application to automatics
Predictor-based stabilization for chained form systems with input time delay
S. Daniar, R. Aazami, M. Shiroei:
Multivariable predictive control considering time delay for load-frequency control in multi-area power systems
Analysis and comparison of the stability of discrete-time and continuous-time linear systems
M. Rachik, M. Lhous:
An observer-based control of linear systems with uncertain parameters
Identification of stable elementary bilinear time-series model
New observer-based control design for mismatched uncertain systems with time-delay
Discrete homing problems
|M. Lefebvre, M. Kounta|
(Ecole Polytechnique, Montreal, Canada)
We consider the so-called homing problem for discrete-time Markov chains. The aim is to optimally control the Markov chain until it hits a given boundary. Depending on a parameter in the cost function, the optimizer either wants to maximize or minimize the time spent by the controlled process in the continuation region. Particular problems are considered and solved explicitly. Both the optimal control and the value function are obtained.
keywords: discrete-time Markov chains, optimal control, principle of optimality, absorption problems
Improving efficiency of pH control by balance-based adaptive control application
|K. Stebel, J. Czeczot, M. Metzger|
(Silesian University of Technology, Poland)
This paper deals with the efficient control of the pH process. Considering the PI + gain scheduling (PI+GS) controller as the benchmark and its control performance as the base, we investigate experimentally the overall improvement in the control performance obtained by the application of the Balance-Based Adaptive Controller (B-BAC), which requires only the measurement data of the flow rates and pH values. The improvement of the control efficiency is investigated not only in terms of the controlled variable performance but also in terms of the manipulated variable performance considered as the considerable control cost. The application of the B-BAController can ensure lower controlled pH variability at the price of the control effort similar to the PI+GS approach and thus it can improve the overall efficiency of pH control. The second important contribution is the experimental validation of the very simple and intuitive tuning procedure for the B-BAController.
keywords: process control, adaptive control, pH process, control efficiency, controller tuning
Robust control of depth of anesthesia based on H∞ design
|D.V. Caiado, J.M. Lemos, B.A. Costa|
(INESC-ID, Lisboa, Portugal)
This paper presents a case study on the design of a robust controller for the depth of anesthesia (DoA) induced by the drug propofol. This process is represented by a linear model together with a non-parametric uncertainty description that is evaluated using a patient model bank with 20 patients undergoing sedation.
By using H∞ methods, the controller is aimed to comply with robust stability and performance specifications for the class of patient models considered. A minimization problem of sensitivity and complementary sensitivity is made to design the controller.
The controller that results from this procedure is approximated by a controller with a lower order, that in turn is redesigned in discrete time for computer control application. The resulting controller is evaluated in simulations using a realistic nonlinear model of DoA.
keywords: depth of anesthesia, model uncertainty, robust control feedback, H∞ design, µ-synthesis
Robust control system design in frequency domain
|V. Veselý, J. Osuský|
(Slovak University of Technology in Bratislava, Slovakia)
In this paper two robust control methods for hybrid system are presented. Both methods are usefull for SISO and MIMO systems. Controller design procedure is developed in frequency domain. Equivalent subsystem method is used for controller design in this paper. Stability condition of proposed methods bases on small gain theory and uses additive and inverse additive model type. Two tank water system is presented in the paper and serves as a numerical example to compare effectiveness of described methods.
keywords: hybrid control, equivalent subsystem method, PI controller
An exponential observer and a controller for a class of nonlinear systems
|M.A. Hammami, M. Zribi, J. Kallel|
(University of Kuwait, Kuwait)
In this paper, we study the observer design problem for a class of nonlinear systems. Specifically, we design an exponential observer for a separately excited DC motor. Moreover, a stabilizing controller is designed for the system to ensure the exponential stability of the solutions toward their desired values. Simulations results show that proposed observer is able to reconstruct the states of the system. In addition, the simulation results indicate that the designed controller works well.
keywords: nonlinear system, observer, stability, controller, stabilization
Real-time implementation of multiple model based predictive control strategy to air/fuel ratio of a gasoline engine
|S. Wojnar, T. Polóni, P. Šimončič, B. Rohal'-Ilkiv, M. Honek, J. Csambál|
(Slovak University of Technology in Bratislava, Slovakia)
Growing safety, pollution and comfort requirements influence automotive industry ever more. The use of three-way catalysts in exhaust aftertreatment systems of combustion engines is essential in reducing engine emissions to levels demanded by environmental legislation. However, the key to the optimal catalytic conversion level is to keep the engine air/fuel ratio (AFR) at a desired level. Thus, for this purposes more and more sophisticated AFR control algorithms are intensively investigated and tested in the literature. The goal of this paper is to present for a case of a gasoline engine the model predictive AFR controller based on the multiple-model approach to the engine modeling. The idea is to identify the engine in particular working points and then to create a global engine's model using Sugeno fuzzy logic. Opposite to traditional control approaches which lose their quality beside steady state, it enables to work with satisfactory quality mainly in transient regimes. Presented results of the multiple-model predictive air/fuel ratio control are acquired from the first experimental real-time implementation on the VW Polo $1390 cm^3$ gasoline engine, at which the original electronic control unit (ECU) has been fully replaced by a dSpace prototyping system which execute the predictive controller. Required control performance has been proven and is presented in the paper.
keywords: model predictive control, multiple models, air/fuel ratio, SI engine, ARX models
Multiphase Z-source inverter using maximum constant boost control
(University Centre of Djelfa, Algeria)
(Texas A\&M University, Qatar)
This paper deals with the impedance source (Z-source) multiphase inverter, where the maximum constant boost control method is studied and analyzed in the general case of number of phases. On the other side the impact of the modulation index and the number of phases on the duty cycle shoot-through and on the gain of the output voltage ranges is presented. To validate advantages of the Z-source multiphase inverter, the proposed topology and the maximum constant boost control are implemented in simulation and in real time experimentation with Z-source five phase inverter. The output voltage is applied to two parallel loads, a five phase resistive load and a five phase induction machine.
keywords: Z-source inverter, multiphase inverter, five phase machine, shoot-through, boost factor, duty cycle