Control of a Projectile Smart Fin Using an Inverse Dynamics-Based Fuzzy Logic Controller

2007 ◽  
Author(s):  
Mohamed B. Trabia ◽  
Woosoon Yim ◽  
Paul Weinacht ◽  
Venkat Mudupu
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Inverse Dynamics ◽  
Operating Conditions ◽  
Attractive Alternative ◽  
Fuzzy Logic Controllers ◽  
Novel Approach ◽  
External Moment ◽  
Element Approach ◽  
Simulation Results

The objective of this paper is to explore a method for the design of fuzzy logic controller for a smart fin used to control the pitch and yaw attitudes of a subsonic projectile during flight. Piezoelectric actuators are an attractive alternative to hydraulic actuators commonly used in this application due to their simplicity. The proposed cantilever-shaped actuator can be fully enclosed within the hollow fin with one end fixed to the rotation axle of the fin while the other end is pinned at the trailing edge of the fin. The paper includes a dynamic model of the system based on the finite element approach. The model includes external moment due to aerodynamic effects. This paper presents a novel approach for automatically creating fuzzy logic controllers for the fin. This approach uses the inverse dynamics of the smart fin system to determine the ranges of the variables of the controllers. Simulation results show that the proposed controller can successfully drive smart fin under various operating conditions.

Inverse Dynamics-Based Fuzzy Logic Control of a Projectile Smart Fin

2005 ◽  
Author(s):  
Mohamed B. Trabia ◽  
Surya Kiran Parimi ◽  
Woosoon Yim
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Control ◽  
Inverse Dynamics ◽  
Operating Conditions ◽  
Attractive Alternative ◽  
Fuzzy Logic Controllers ◽  
Logic Control ◽  
Novel Approach ◽  
External Moment ◽  
Element Approach

A smart fin for a subsonic projectile should be able to produce maneuvering force and moment that can control its rotation during flight. Piezoelectric actuator is an attractive alternative to usual hydraulic actuators due to its simplicity. The cantilever-shaped actuator can also be fully enclosed within the hollow fin. It has an end fixed to the rotation axle of the fin while the other end is pinned at the tip of the fin. A dynamic model of the system, including external moment due to aerodynamic effects, is obtained using the finite element approach. This paper presents a novel approach for automatically creating fuzzy logic controllers for the fin. This approach uses the inverse dynamics of the smart fin system to determine the ranges of the variables of the controllers. Simulation results show that the proposed controller can successfully drive smart fin under various operating conditions.

A Single Phase Anti-Swing Fuzzy Logic Controller for an Overhead Crane With Hoisting

2006 ◽  
Author(s):  
Mohamed B. Trabia ◽  
Jamil M. Renno ◽  
Kamal A. F. Moustafa
Keyword(s):  
Fuzzy Logic ◽  
Single Phase ◽  
Fuzzy Logic Controller ◽  
Inverse Dynamics ◽  
Operating Conditions ◽  
Overhead Crane ◽  
Fuzzy Logic Controllers ◽  
Overhead Cranes ◽  
Novel Approach ◽  
Logic Controllers

This paper presents a novel approach for automatically creating anti-swing fuzzy logic controllers for overhead cranes with hoisting. This approach uses the inverse dynamics of the overhead crane to determine the ranges of the variables of the controllers. The control action is distributed among three fuzzy logic controllers (FLCs): travel controller, hoist controller, and anti-swing controller. Simulation examples show that the proposed controller can successfully drive overhead cranes under various operating conditions.

GA-Based Fuzzy Logic Control for a Smart Fin of a Projectile

2007 ◽  
Author(s):  
Venkat Mudupu ◽  
Mohamed B. Trabia ◽  
Woosoon Yim ◽  
Paul Weinacht
Keyword(s):  
Fuzzy Logic ◽  
System Identification ◽  
Fuzzy Logic Control ◽  
Fuzzy Logic Controller ◽  
Operating Conditions ◽  
Piezoelectric Bimorph ◽  
Logic Control ◽  
Identification Technique ◽  
Simulation Results ◽  
Design And Testing

This paper presents the design and testing of a smart fin for a subsonic projectile. The smart fin is activated using a piezoelectric bimorph with a substrate that is completely enclosed within the fin. A linear model of the actuator and fin system is created using the frequency response identification technique within MATLAB System Identification Toolbox. A procedure for designing a GA-based fuzzy logic controller for the fin is presented. Experimental and simulation results show that the proposed controller achieved the fin angle control under different operating conditions.

Genetic algorithms with variable mutation rates: Application to fuzzy logic controller design

1997 ◽  
Vol 211 (2) ◽  
pp. 157-167 ◽  
Author(s):  
D T Pham ◽  
D Karaboga
Keyword(s):  
Genetic Algorithms ◽  
Fuzzy Logic ◽  
Mutation Rate ◽  
Fuzzy Logic Controller ◽  
Controller Design ◽  
Mutation Rates ◽  
Fuzzy Logic Controllers ◽  
Delayed System ◽  
Simulation Results ◽  
Logic Controllers

Three variable mutation rate strategies for improving the performance of genetic algorithms (GAs) are described. The problem of optimizing fuzzy logic controllers is used to evaluate a GA adopting these strategies against a GA employing a static mutation regime. Simulation results for a second-order time-delayed system controlled by fuzzy logic controllers (FLCs) obtained using the different GAs are presented.

scholarly journals COMPARATIVE STUDY OF MAMDANI AND 1 ST -ORDER TAKAGI SUGENO KANG TYPE FUZZY LOGIC CONTROLLERS FOR CONTROLLING THE RIGID GANTRY CRANE SYSTEM

2018 ◽  
Vol 40 (2) ◽  
pp. 57
Author(s):  
Edwar Yazid ◽  
Rifa Rahmayanti
Keyword(s):  
Fuzzy Logic ◽  
Comparative Study ◽  
Rise Time ◽  
Fuzzy Logic Controller ◽  
Settling Time ◽  
Gantry Crane ◽  
Peak Time ◽  
Fuzzy Logic Controllers ◽  
Simulation Results ◽  
Takagi Sugeno

Controlling the rigid gantry crane system is challenging due to it being an under-actuated system. This paper addresses the challenge by presenting the fuzzy logic controller (FLC) with Mamdani and the 1 st -order Takagi Sugeno Kang (TSK) types presenting it in this comparative study. Both controllers are proposed to control the position of the crane while suppressing the swing of the payload. Simulation results show that the Mamdani type outperforms the 1 st -order Takagi Sugeno Kang (TSK) type in terms of no overshoot, though the earlier controller (Mamdani) has a slower rise time, settling time and peak time than the latter controller (TSK).

scholarly journals Implementation of Type-2 Fuzzy Logic Controller in PMSM Drives Using DSP

2018 ◽  
Vol 9 (3) ◽  
pp. 1098 ◽  
Author(s):  
Said Wahsh ◽  
Y. Ahmed ◽  
Abo Elzahab
Keyword(s):  
Fuzzy Logic ◽  
Steady State ◽  
Fuzzy Logic Controller ◽  
Permanent Magnet Synchronous Motor ◽  
Digital Signal ◽  
Operating Conditions ◽  
Simulation Results ◽  
Interval Type ◽  
Short Time

This paper presents interval type-2 fuzzy logic (IT2FL) controller applied on a direct torque controlled (DTC) permanent magnet synchronous motor (PMSM), using digital signal processing (DSP). The simulation of PMSM with space vector pulse widths modulation (SVPWM) inverter presented under several operating condition. To verify the simulation results a hard ware setup is prepared and tested at several operating conditions using dspace 1102 DSP model.  The experimental and simulation results are in agreement and the torque dynamic response is very rapid and the system achieves the steady state in a very short time.

Artificial Neural Networks Used As a Rule Selector for Fuzzy Logic Controllers

1993 ◽  
Author(s):  
Shou-Heng Huang ◽  
Ron M. Nelson
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Absolute Error ◽  
Operating Conditions ◽  
Delta Rule ◽  
Rule Sets ◽  
Artificial Neural ◽  
Artificial Neural Network Ann ◽  
Set Up ◽  
And Control

Abstract A feedforward, three-layer, partially-connected artificial neural network (ANN) is proposed to be used as a rule selector for a rule-based fuzzy logic controller. This will allow the controller to adapt to various control modes and operating conditions for different plants. A principal advantage of an ANN over a look up table is that the ANN can make good estimates to fill in for missing data. The control modes, operating conditions, and control rule sets are encoded into binary numbers as the inputs and outputs for the ANN. The General Delta Rule is used in the backpropagation learning process to update the ANN weights. The proposed ANN has a simple topological structure and results in a simple analysis and relatively easy implementation. The average square error and the maximal absolute error are used to judge if the correct connections between neurons are set up. Computer simulations are used to demonstrate the effectiveness of this ANN as a rule selector.

scholarly journals Mat lab/simulink based fault analysis of pv grid with intelligent fuzzy logic control mppt

2018 ◽  
Vol 7 (2.12) ◽  
pp. 198
Author(s):  
Neeraj Priyadarshi ◽  
Amarjeet Kr. Sharma ◽  
Akash Kr. Bhoi ◽  
S N. Ahmad ◽  
Farooque Azam ◽  
...  
Keyword(s):  
Fuzzy Logic ◽  
Power System ◽  
Fuzzy Logic Controller ◽  
Fault Analysis ◽  
Operating Conditions ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Hysteresis Controller ◽  
Power Point ◽  
Pv Grid

This paper mainly presents the fault analysis of Photovoltaic (PV) grid power system. The fuzzy logic controller (FLC) based intelligent maximum power point tracking (MPPT) algorithm has been employed in this work. Moreover, the hysteresis controller has been implemented for inverter control. Simulation results based on MATLAB/SIMULINK justify the effectiveness of the proposed PV power system under different fault operating conditions. 

scholarly journals Embedded Fuzzy Based Boiler Control

2016 ◽  
Vol 5 (2) ◽  
pp. 105
Author(s):  
Celin S
Keyword(s):  
Fuzzy Logic ◽  
Embedded System ◽  
Power Plants ◽  
Operating Conditions ◽  
Project Work ◽  
Feed Water ◽  
Steam Temperature ◽  
Fuzzy Logic Controllers ◽  
Power Station ◽  
Fuzzy Logic Technique

<p>Boiler control in a power station is a very important criteria in regulation of uninterrupted electricity. In existing power plants, the control of its features and parameters are done by PI and PD controllers. The parameters that control the regulation of boiler conduction are drum level, steam flow, feed water flow, steam temperature and light intensity. It is necessary to produce the steam required to run the generator. When the load in the generator changes, there must be corresponding change in the steam volume. This may cause adverse effect in the boiler. In order to avoid the effect in the boiler, the parameters mentioned above must be maintained constant, which is attained by regulating the corresponding valves. This project work has a feasibility of using fuzzy logic controllers in the place of conventional controllers is done by using embedded system. It is found that the rule based fuzzy logic technique can be implemented by stringent operating conditions. </p>

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