DIRECT ADAPTIVE TYPE-2 FUZZY CONTROL FOR NONLINEAR SYSTEMS

2006 ◽  
Vol 06 (03) ◽  
pp. 389-411 ◽  
Author(s):  
KHEIREDDINE CHAFAA ◽  
LAMIR SAIDI ◽  
MOUNA GHANAI ◽  
KHIER BENMAHAMMED
Keyword(s):  
Fuzzy Controller ◽  
Tracking Error ◽  
Nonlinear Dynamical System ◽  
Reference Trajectory ◽  
Oscillation System ◽  
Control Effort ◽  
Nonlinear Dynamical ◽  
Supervisory Controller ◽  
And Control

A new direct adaptive type-2 fuzzy controller for a nonlinear dynamical system is developed in this paper. The parameters of the membership functions characterizing the linguistic terms in the type-2 fuzzy IF–THEN rules change according to some adaptive law for the purpose of controlling a plant to track a reference trajectory. A supervisory controller is appended to the type-2 fuzzy controller to force the state to be within the constraint set. Stability of this adaptive scheme is established using Lyapunov stability tools, where we guarantee the global stability of the resulting closed-loop system, in the sense that all signals involved are uniformly bounded. The simulation results for a Duffing forced-oscillation system show better performances, i.e. tracking error and control effort can be made smaller.

Design of GA-Based Control for Electrical Servo Drive

2011 ◽  
Vol 201-203 ◽  
pp. 2375-2378
Author(s):  
Kuo Ho Su ◽  
Feng Hsiang Hsiao
Keyword(s):  
Genetic Algorithm ◽  
Gradient Descent ◽  
Nonlinear Dynamical System ◽  
Servo Drive ◽  
Control Effort ◽  
Nonlinear Dynamical ◽  
Supervisory Controller ◽  
Control Scheme ◽  
Control Schemes ◽  
System States

An alternative control scheme including a directional genetic algorithm controller (DGAC) and a supervisory controller is developed to control the position of an electrical servo drive in this study. In the DGAC design, the spirit of gradient descent training is embedded in genetic algorithm (GA) to construct a main controller to search optimum control effort under possible occurrence of uncertainties. In order to ensure the system states around a defined bound region, a supervisory controller, which is derived in the sense of Lyapunov stability theorem, is added to adjust the control effort. Compared with enunciated GA control methods, the proposed control scheme possesses some salient advantages of simple framework, fewer executing time and good self-organizing properties even for nonlinear dynamical system. The effectiveness is demonstrated by simulation results, and its advantages are indicated in comparison with other GA control schemes for a field-oriented control induction motor drive.

Adaptive Hybrid Intelligent Tracking Control for Uncertain Fractional Order Chaotic Systems

2012 ◽  
Vol 1 (1) ◽  
pp. 1-16 ◽  
Author(s):  
Tsung-Chih Lin ◽  
Chia-Hao Kuo
Keyword(s):  
Fractional Order ◽  
Chaotic Systems ◽  
Fuzzy Controller ◽  
Tracking Error ◽  
Adaptive Fuzzy Control ◽  
Weighting Factor ◽  
Control Effort ◽  
Plant Knowledge ◽  
Control Knowledge ◽  
And Control

This paper presents an adaptive hybrid fuzzy controller to achieve prescribed tracking performance of fractional order chaotic systems. Depending on plant knowledge and control knowledge, a weighting factor can be adjusted by combining the indirect adaptive fuzzy control effort and the direct fuzzy adaptive control effort. Nonlinear fractional order chaotic response system is fully demonstrated to track the trajectory generated from fractional order chaotic drive system. The numerical results show that tracking error and control effort can be made smaller and the proposed hybrid intelligent control scheme is more flexible during the design process.

scholarly journals Robust Tracker of Hybrid Microgrids by the Invariant-Ellipsoid Set

Electronics ◽  
2021 ◽  
Vol 10 (15) ◽  
pp. 1794
Author(s):  
Hilmy Awad ◽  
Ehab H. E. Bayoumi ◽  
Hisham M. Soliman ◽  
Michele De Santis
Keyword(s):  
Sliding Mode ◽  
Tracking Error ◽  
Nonlinear Dynamical System ◽  
Sufficient Conditions ◽  
Linear Matrix ◽  
Nonlinear Dynamical ◽  
Load Variations ◽  
Invariant Ellipsoid ◽  
Steady State Responses ◽  
Linearized Model

This paper introduces a new ellipsoidal-based tracker design to control a grid-connected hybrid direct current/alternating current (DC/AC) microgrid (MG). The proposed controller is robust against both parameters and load variations. The studied hybrid MG is modelled as a nonlinear dynamical system. A linearized model around an operating point is developed. The parameter changes are modelled as norm-bounded uncertainties. We apply the new extended version of the attractive (or invariant) ellipsoid for this tracking problem. Convex optimization is used to obtain the region’s minimal size where the tracking error between the state trajectories and the reference states converges. The sufficient conditions for stability are derived and solved based on linear matrix inequalities (LMIs). The proposed controller’s validity is shown via simulating the hybrid MG with various operational scenarios. In each scenario, the performance of the controller is compared with a recently proposed sliding mode controller. The comparison clearly illustrates the superiority of the developed controller in terms of transient and steady-state responses.

Stabilization of Periodic Flap-Lag Dynamics in Rotor Blades

1995 ◽  
Author(s):  
John M. Schmitt ◽  
Philip V. Bayly ◽  
David A. Peters
Keyword(s):  
Nonlinear Dynamical System ◽  
Rotor Blades ◽  
Discrete Control ◽  
System Control ◽  
Transient Effects ◽  
Control Effort ◽  
Nonlinear Dynamical ◽  
Helicopter Rotor Blades ◽  
Stable Periodic ◽  
The Stability

Abstract A method to increase the stability of periodic flap-lag dynamics in helicopter rotor blades is investigated. Instability in the flap-lag dynamics of stiff-in-plane rotors can occur as forward flight speed is increased, or if significant pitch-lag coupling is present. A method originally developed to control chaos can be applied to stabilize unstable or weakly stable periodic behavior. Stabilization is achieved using small perturbations of the mean blade pitch angle. The approach, which will be referred to as periodic active control (PAC), consists of applying discrete control to the Poincaré map associated with the nonlinear dynamical system. Control effort is applied efficiently, since it does not change, but only stabilizes underlying periodic motion. Stabilization can lead to higher safe speeds, decreased transient effects, and simplified designs in helicopters.

Path tracking control of electromechanical micro-positioner by considering control effort of the system

2020 ◽  
pp. 095965182095327
Author(s):  
Mohammad Reza Gharib ◽  
Ali Koochi ◽  
Mojtaba Ghorbani
Keyword(s):  
Tracking Control ◽  
Tracking Error ◽  
Path Tracking ◽  
Lumped Parameter Model ◽  
Proportional Integral Derivative ◽  
Control Effort ◽  
Proportional Integral Derivative Controller ◽  
Proportional Integral ◽  
Micro Actuators ◽  
And Control

Position controlling with less overshoot and control effort is a fundamental issue in the design and application of micro-actuators such as micro-positioner. Also, tracking a considered path is very crucial for some particular applications of micro-actuators such as surgeon robots. Herein, a proportional–integral–derivative controller is designed using a feedback linearization technique for path tracking control of a cantilever electromechanical micro-positioner. The micro-positioner is simulated based on a 1-degree-of-freedom lumped-parameter model. Three different paths are considered, and the capability of the designed controller on the path tracking with lower error and control effort is investigated. The obtained results demonstrate the efficiency of the designed proportional–integral–derivative controller not only for reducing the tracking error but also for decreasing the control effort.

Fuzzy Logic Real-Time Digital Control of a Hardware in the Loop Maglev Device Using MATLAB and xPC Target

2003 ◽  
Author(s):  
O. Taghavi ◽  
P. S. Shiakolas ◽  
O. Kuljaca
Keyword(s):  
Fuzzy Logic ◽  
Real Time ◽  
Digital Control ◽  
Magnetic Levitation ◽  
Tracking Error ◽  
Open Loop ◽  
Reference Trajectory ◽  
Hardware In The Loop ◽  
Time Data ◽  
Control Effort

This work will discuss the use of a single environment for real-time digital control with a hardware-in-the-loop (HIL) magnetic levitation (maglev) device for modeling and controls education, with emphasis on fuzzy logic (FL) feedforward control. This environment utilizes two computers (host and target), an off-the-shelf data acquisition card, and the HIL device (a nonlinear, open-loop, unstable, and time varying, custom-built maglev). The software includes tools from MathWorks Inc., and a C++ compiler. The values of any parameter (control law, reference trajectory) in the Smulink model can be changed dynamically on the host computer and their effects observed in real-time on the HIL system. Real-time data was collected from the HIL device and used in designing, tuning and implementing a feedforward FL controller all using MathWorks tools that controlled the HIL device in real-time. It was observed that the tracking error was substantially improved when the FL augmented the control effort of a classical lead compensator. The procedure for the FL development, tuning and hardware implementation along with examples will be presented. This system has been recently completed and was successfully used in an educational setting for one graduate and undergraduate Mechanical Engineering course.

Fuzzy Multivariable Control Strategy Applied to a Refrigeration System

2016 ◽  
Vol 12 (2) ◽  
Author(s):  
Saulo Fernando dos Santos Vidal ◽  
Jones Erni Schmitz ◽  
Ivan Carlos Franco ◽  
Ana Maria Frattini Fileti ◽  
Flavio Vasconcelos Da Silva
Keyword(s):  
Energy Consumption ◽  
Fuzzy Controller ◽  
Fine Tuning ◽  
Refrigeration System ◽  
Process Variables ◽  
Pump Frequency ◽  
Comparative Performance ◽  
Control Effort ◽  
Squared Error ◽  
And Control

Abstract The refrigeration process involves complex systems exhibiting nonlinearities and coupled behavior, so this paper aims to evaluate the comparative performance of a multivariable fuzzy logic-based control system and a classic multi loop PID. The process variables were the temperature of the secondary fluid (propylene glycol) outlet and the evaporating temperature. The manipulated variables were the compressor frequency speed and the pump frequency speed. Aspen Plus and Aspen Dynamics simulators were used to simulate the experimental prototype. The model was previously validated and linked with MATLAB software, where the controllers were implemented. Tuning of the fuzzy controller was performed through the membership functions and gains adjustments. The tuning of the multi loop PID controller was performed using the Ziegler-Nichols method and then a fine tuning was carried out. In order to fairly compare energy consumption and control effort, the tune of PID-based strategy was finished when similar values of Integral of Squared Error were achieved. Thus, very similar behavior for the process variables in both controllers. On the other hand, a great improvement in the control effort and energy saving was observed when the multivariable fuzzy controller was used in comparison to classic PID. The energy consumption was reduced by 25 % and the control effort by 96 % when the proposed strategy was used.

scholarly journals Uncertain Fractional Order Chaotic Systems Tracking Design via Adaptive Hybrid Fuzzy Sliding Mode Control

2011 ◽  
Vol 6 (3) ◽  
pp. 418 ◽  
Author(s):  
Tsung-Chih Lin ◽  
Chia-Hao Kuo ◽  
Valentina E. Balas
Keyword(s):  
Sliding Mode Control ◽  
Fractional Order ◽  
Chaotic Systems ◽  
Fuzzy Controller ◽  
Sliding Mode ◽  
Tracking Error ◽  
Adaptive Fuzzy Controller ◽  
Adaptive Fuzzy ◽  
Mode Control ◽  
And Control

In this paper, in order to achieve tracking performance of uncertain fractional order chaotic systems an adaptive hybrid fuzzy controller is proposed. During the design procedure, a hybrid learning algorithm combining sliding mode control and Lyapunov stability criterion is adopted to tune the free parameters on line by output feedback control law and adaptive law. A weighting factor, which can be adjusted by the trade-off between plant knowledge and control knowledge, is adopted to sum together the control efforts from indirect adaptive fuzzy controller and direct adaptive fuzzy controller. To confirm effectiveness of the proposed control scheme, the fractional order chaotic response system is fully illustrated to track the trajectory generated from the fractional order chaotic drive system. The numerical results show that tracking error and control effort can be made smaller and the proposed hybrid intelligent control structure is more flexible during the design process.

Chaos Behavior and Control of Stay-Cables

2012 ◽  
Vol 446-449 ◽  
pp. 1109-1114
Author(s):  
Jin Hai Li ◽  
Qing Li Yan ◽  
Jin Shuan Liu
Keyword(s):  
Dynamic Behavior ◽  
Chaotic Motion ◽  
Nonlinear Dynamical System ◽  
Melnikov Method ◽  
Periodic Excitation ◽  
Stay Cable ◽  
Nonlinear Dynamical ◽  
Infinite Dimensional ◽  
First Order ◽  
And Control

Stay-cable is infinite dimensional nonlinear dynamical system with a very complex vibration types and mechanism which are not described reasonably yet. In order to better control its dynamic behavior, it is necessary to study complex dynamic behavior carefully. Fistly, partial differential equation of the cable motion is established based on the parabolic initial configuration and is simplified into n Duffing-equations by using Galerkin method. Secondly, the chaos behaviors of the first order Duffing-equation under periodic excitation are studied by taking advantage of Melnikov method. At last , parameters may lead to chaotic motion of a true cable in laboratory are calculated and the methods of chaos control are discussed briefly. The study shows that: 1. First order vibration of cable under periodic excitation has much more complex behaviors than the freedom vibration; 2. The Melnikov method can be very effective and convenient for the analysis of chaotic motion of cable.

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