scholarly journals Gain scheduled controller design for thermo-optical plant

2014 ◽  
Vol 24 (3) ◽  
pp. 333-349 ◽  
Author(s):  
Vojtech Veselý ◽  
Jakub Osuský ◽  
Ivan Sekaj
Keyword(s):  
Output Feedback ◽  
Closed Loop ◽  
Controller Design ◽  
Design Method ◽  
Feedback Gain ◽  
Small Gain ◽  
Gain Scheduled Controller ◽  
The Stability ◽  
Gain Scheduled ◽  
Siso Systems

Abstract This paper presents a gain scheduled controller design for MIMO and SISO systems in the frequency domain using the genetic algorithms approach. The proposed method is derived from the M-delta structure of closed loop MIMO (SISO) systems and the small gain theory is exploited to obtain the stability condition. An example of real system illustrates the effectiveness of the proposed output feedback gain scheduled controller design method and also the possibility to improve its performance using the genetic algorithm

scholarly journals Reducing the mast vibration of single-mast stacker cranes by gain-scheduled control

2016 ◽  
Vol 26 (4) ◽  
pp. 791-802 ◽  
Author(s):  
Sándor Hajdu ◽  
Péter Gáspár
Keyword(s):  
Dynamic Modeling ◽  
Controller Design ◽  
Design Method ◽  
Dynamic Properties ◽  
Dynamical Behavior ◽  
Reference Signal ◽  
Frame Structure ◽  
Signal Tracking ◽  
Gain Scheduled Controller ◽  
Gain Scheduled

AbstractIn the frame structure of stacker cranes harmful mast vibrations may appear due to the inertial forces of acceleration or the braking movement phase. This effect may reduce the stability and positioning accuracy of these machines. Unfortunately, their dynamic properties also vary with the lifted load magnitude and position. The purpose of the paper is to present a controller design method which can handle the effect of a varying lifted load magnitude and position in a dynamic model and at the same time reveals good reference signal tracking and mast vibration reducing properties. A controller design case study is presented step by step from dynamic modeling through to the validation of the resulting controller. In the paper the dynamic modeling possibilities of single-mast stacker cranes are summarized. The handling of varying dynamical behavior is realized via the polytopic LPV modeling approach. Based on this modeling technique, a gain-scheduled controller design method is proposed, which is suitable for achieving the goals set. Finally, controller validation is presented by means of time domain simulations.

LMI-Based Decentralized PID Controller Design With Application to the Shape Control of Magnetic Fluid Deformable Mirrors

2010 ◽  
Author(s):  
Zhizheng Wu ◽  
Azhar Iqbal ◽  
Foued Ben Amara
Keyword(s):  
Adaptive Optics ◽  
Output Feedback ◽  
Pid Controller ◽  
Control Algorithm ◽  
Closed Loop ◽  
Controller Design ◽  
Design Method ◽  
Pid Controller Design ◽  
Static Output ◽  
Adaptive Optics System

In this paper, a decentralized robust PID controller design method is proposed for multi-input multi-output systems. The system model is first decoupled in the low frequency range, and only the diagonal entries in the DC-decoupled plant model are retained. To deal with the resulting unmodeled high frequency dynamics, a decentralized robust PID controller design method is proposed, where the robust stability and transient response performance of the resulting closed loop system are formulated as a multi-objective H∞/H2 static output feedback problem. The desired parameters of the PID controller are determined by solving a static output feedback problem using linear matrix inequalities (LMIs). Finally, the performance of the proposed control algorithm is experimentally evaluated on the adaptive optics system involving a prototype magnetic fluid deformable mirror (MFDM). The experimental results illustrate the effectiveness of the proposed control algorithm for the MFDM surface shape tracking in the closed loop adaptive optics system.

Advanced gain scheduledH∞controller for robotic manipulators

Robotica ◽  
2002 ◽  
Vol 20 (5) ◽  
pp. 537-544
Author(s):  
Zhongwei Yu ◽  
Huitang Chen ◽  
Peng-Yung Woo
Keyword(s):  
Output Feedback ◽  
Closed Loop ◽  
Controller Design ◽  
Robotic Manipulators ◽  
Linear Matrix ◽  
Matrix Inequalities ◽  
Vertex Set ◽  
Parameter Dependent ◽  
Gain Scheduled ◽  
Upper Boundary

SummaryA conservatism-reduced design of a gain scheduled output feedbackH∞controller for ann-joint rigid robotic manipulator, which integrates the varying-parameter rate without their feedback, is proposed. The robotic system is reduced to a 1inear parameter varying (LPV) form, which depends on the varying-parameter. By using a parameter-dependent Lyapunov function, the design of a controller, which satisfies the closed-loopH∞performance, is reduced to a solution of the parameterized linear matrix inequalities (LMIs) of parameter matrices. With a use of the concept of “multi-convexity”, the solution of the infinite LMIs in the varying-parameter and its rate space is reduced to a solution of the finite LMIs for the vertex set. The proposed controller eliminates the feedback of the varying-parameter rate and fixes its upper boundary so that the conservatism of the controller design is reduced. Experimental results verify the effectiveness of the proposed design.

scholarly journals H∞Gain-Scheduled Control for LPV Stochastic Systems

2015 ◽  
Vol 2015 ◽  
pp. 1-14 ◽  
Author(s):  
Cheung-Chieh Ku ◽  
Guan-Wei Chen
Keyword(s):  
Stochastic Systems ◽  
Weighting Function ◽  
Design Method ◽  
Sufficient Conditions ◽  
Linear Matrix ◽  
Mean Square ◽  
Gain Scheduled Controller ◽  
The Stability ◽  
Uncertain Stochastic System ◽  
Gain Scheduled

A robust control problem for discrete-time uncertain stochastic systems is discussed via gain-scheduled control scheme subject toH∞attenuation performance. Applying Linear Parameter Varying (LPV) modeling approach and stochastic difference equation, the uncertain stochastic systems can be described by combining time-varying weighting function and linear systems with multiplicative noise terms. Due to the consideration of stochastic behavior, the stability in the sense of mean square is applied for the system. Furthermore, two kinds of Lyapunov functions are employed to derive their corresponding sufficient conditions to solve the stabilization problems of this paper. In order to use convex optimization algorithm, the derived conditions are converted into Linear Matrix Inequality (LMI) form. Via solving those conditions, the gain-scheduled controller can be established such that the robust asymptotical stability andH∞performance of the disturbed uncertain stochastic system can be achieved in the sense of mean square. Finally, two numerical examples are applied to demonstrate the effectiveness and applicability of the proposed design method.

scholarly journals Stability of a Class of Stochastic Nonlinear Systems with Markovian Switching

2015 ◽  
Vol 2015 ◽  
pp. 1-7
Author(s):  
Xiaohua Liu ◽  
Wuquan Li
Keyword(s):  
Nonlinear Systems ◽  
Output Feedback ◽  
Closed Loop ◽  
Design Method ◽  
Feedback Controller ◽  
Markovian Switching ◽  
Stochastic Nonlinear Systems ◽  
Closed Loop System ◽  
Output Feedback Controller ◽  
The Stability

This paper investigates the stability of a class of stochastic nonlinear systems with Markovian switching via output-feedback. Based on the backstepping design method and homogeneous domination technique, an output-feedback controller is constructed to guarantee that the closed-loop system has a unique solution and is almost surely asymptotically stable. The efficiency of the output-feedback controller is demonstrated by a simulation example.

Gain-Scheduled H∞ Control for Linear Parameter Varying Stochastic Systems

2015 ◽  
Vol 137 (11) ◽  
Author(s):  
Cheung-Chieh Ku ◽  
Cheng-I Wu
Keyword(s):  
Stochastic Systems ◽  
Controller Design ◽  
Design Method ◽  
Sufficient Conditions ◽  
Linear Matrix ◽  
Linear Parameter ◽  
Linear Parameter Varying ◽  
Parameter Varying ◽  
Gain Scheduled Controller ◽  
Gain Scheduled

In this paper, a gain-scheduled controller design method is proposed for linear parameter varying (LPV) stochastic systems subject to H∞ performance constraint. Applying the stochastic differential equation, the stochastic behaviors of system are described via multiplicative noise terms. Employing the gain-scheduled design technique, the stabilization problem of LPV stochastic systems is discussed. Besides, the H∞ attenuation performance is employed to constrain the effect of external disturbance. Based on the Lyapunov function and Itô's formula, the sufficient conditions are derived to propose the stability criteria for LPV stochastic systems. The derived sufficient conditions are converted into linear matrix inequality (LMI) problems that can be solved by using convex optimization algorithm. Through solving these conditions, the gain-scheduled controller can be obtained to guarantee asymptotical stability and H∞ performance of LPV stochastic systems. Finally, numerical examples are provided to demonstrate the applications and effectiveness of the proposed controller design method.

scholarly journals WGC Based Robust and Gain Scheduling PI Controller Design for Condensing Boilers

2014 ◽  
Vol 6 ◽  
pp. 659051 ◽  
Author(s):  
Cem Onat
Keyword(s):  
Water Flow ◽  
Flow Rate ◽  
Closed Loop ◽  
Controller Design ◽  
Water Flow Rate ◽  
Pi Controller ◽  
Main Challenge ◽  
Wide Range ◽  
The Stability ◽  
Gain Scheduled

This paper addresses the water temperature PI control in condensing domestic boilers. The main challenge of this process under the controller design perspective is the fact that the dynamics of condensing boilers are strongly affected by the demanded water flow rate. First, a robust PI controller based on weighted geometrical center method is designed that stabilizes and achieves good performance for closed-loop system for a wide range of the water flow rate. Then, it is shown that if the water flow rate information is used to update the controller gains, through a technique known as gain scheduled control, the performance can be significantly improved. Important characteristics of these PI design approaches are that the resulting parameters are calculated numerically without using any graphical method or iterative optimization process and that it guarantees the stability of the closed-loop. Significantly, simulation results have demonstrated that the proposed tuning techniques can perform better for set point changes and load disturbance than other available methods in the literature.

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