Hybrid fuzzy and sliding-mode control for motorised tether spin-up when coupled with axial vibration

A hybrid fuzzy sliding mode controller is applied to the control of motorised tether spin-up coupled with an axial oscillation phenomenon. A six degree of freedom dynamic model of a motorised momentum exchange tether is used as a basis for interplanetary payload exchange. The tether comprises a symmetrical double payload configuration, with an outrigger counter inertia and massive central facility. It is shown that including axial elasticity permits an enhanced level of performance prediction accuracy and a useful departure from the usual rigid body representations, particularly for accurate payload positioning at strategic points. A special simulation program has been devised in MATLAB and MATHEMATICA for a given initial condition data case

Hybrid fuzzy sliding mode control for motorised space tether spin-up when coupled with axial and torsional oscillation

A specialised hybrid controller is applied to the control of a motorised space tether spin-up space coupled with an axial and a torsional oscillation phenomenon. A seven-degree-of-freedom (7-DOF) dynamic model of a motorised momentum exchange tether is used as the basis for interplanetary payload exchange in the context of control. The tether comprises a symmetrical double payload configuration, with an outrigger counter inertia and massive central facility. It is shown that including axial and torsional elasticity permits an enhanced level of performance prediction accuracy and a useful departure from the usual rigid body representations, particularly for accurate payload positioning at strategic points. A simulation with given initial condition data has been devised in a connecting programme between control code written in MATLAB and dynamics simulation code constructed within MATHEMATICA. It is shown that there is an enhanced level of spin-up control for the 7-DOF motorised momentum exchange tether system using the specialised hybrid controller. hybrid controller

Linear, integer separable and fuzzy programming problems: a united approach towards automatic reformulation

For mathematical programming (MP) to have greater impact as a decision tool, MP software systems must offer suitable support in terms of model communication and modelling techniques. In this paper modelling techniques that allow logical restrictions to be modelled in integer programming terms are described and their implications discussed. In addition it is demonstrated that many classes of non-linearities which are not variable separable may be after suitable algebraic manipulation put in a variable separable form. The methods of reformulating the fuzzy linear programming problem as a Max-Min problem is also introduced. It is shown that analysis of bounds plays a key role in the following four important contexts: model reduction, reformulation of logical restrictions as 0-1 mixed integer programs, reformulation of nonlinear programs as variable separable programs and reformulation of fuzzy linear programs. It is observed that as well as incorporating an interface between the modeller and the optimiser there is a need to make available to the modeller software facilities which support the model reformulation techniques described here

Fuzzy approach for risk assessment of brominated flame retardants in aquatic ecosystems

Brominated flame retardants (BFR) are pollutants that represent a threat to both human health and environment due to their industrial use, their persistence and their ability to bioaccumulate and biomagnify in food chains, especially in the aquatic one. For the last ten years contamination levels for this type of compounds have been reported for European, North American and Asian human tissue, sediments and biota samples [1-3]. However, monitoring efforts into the assessment of BFRs contamination levels in Latin America are scarce. In this study, a model for the evaluation of the environmental risk of BFRs in the aquatic ecosystems has been developed. It has been based on a technical application of the Fuzzy Theory [4]. In particular, three interconnected Fuzzy Inference Systems (FIS) have been created through the use of the Fuzzy Toolbox in Matlab. In order to improve and make the model scientifically robust, several international experts have been questioned about different information required to build the fuzzy system. Information from 38 questionnaires have been collected and statistically treated.Preprin

Effectiveness of repair method using hybrid fiber reinforced polymer fabric on concrete-filled double skin steel tubular columns exposed to fire

Concrete-filled double skin steel tubular (CFDST) columns were often used in outdoor construction where fire is not a main concern. Therefore, this series of research deals with behaviour of CFDST columns after fire exposure, residual strength and method of repairing fire-damaged columns. This particular paper focused on the effectiveness of Hybrid Fiber Reinforced Polymer (FRP) repairing method. Total of 42 specimens were casted and 36 of the specimens were exposed to ASTM E-119 until the temperature of 600˚C. After that, the temperature was kept constant for 60 and 90 minutes. Out of 36 specimens that were exposed to fire, 24 of the specimens were repaired with FRP using hand lay-up method. All of the specimens (control, heated unrepaired and heated repaired) were subjected to concentric axial loading. It was found that by using Hybrid FRP, the ultimate strength at failure of repaired specimens greatly increased when compared to fire-damaged specimens to the extent of exceeding the control specimens. In addition, FRP is also effectively confined thinner outer steel tube than thicker outer steel tube. However, the effectiveness of Hybrid FRP repair method depends on several factor such as thickness of outer steel tube and maximum exposure time

Modelling and Simulation for Industrial DC Motor Using Intelligent Control

AbstractThis paper presents an overview of Proportional Integral control (PI) and Artificial Intelligent control (AI) algorithms. AI and PI controller are analyzed using Matlab [Simulink] software. The DC motor is an attractive piece of equipment in many industrial applications requiring variable speed and load characteristics due to its ease of controllability. The main objective of this paper illustrates how the speed of the DC motor can be controlled using different controllers. The simulation results demonstrate that the responses of DC motor with an AI control which is Fuzzy Logic Control shows satisfactory well damped control performance. The results shows that Industrial DC Motor model develop using its physical parameters and controlled with an AI controller give better response, it means it can used as a controller to the real time DC Moto

NCTF-FL Controller for Pendulum Balancing System

Pendulum Balancing of Linear Servo System consists of a cart driven by a DC motor, via a rack and pinion mechanism to ensure consistent and continuous traction. The cart is also equipped with a rotary joint to which a free turning rod (or pendulum) can be attached. This concept paper proposed a combination of Nominal Characteristic Trajectory Following (NCTF) and Fuzzy Logic (FL) to control the position of the cart and to balance the pendulum. The proposed controllers are expected to have a simple design method and achieved high performances

NCTF-FL Controller for Pendulum Balancing System

Pendulum Balancing of Linear Servo System consists of a cart driven by a DC motor, via a rack and pinion mechanism to ensure consistent and continuous traction. The cart is also equipped with a rotary joint to which a free turning rod (or pendulum) can be attached. This concept paper proposed a combination of Nominal Characteristic Trajectory Following (NCTF) and Fuzzy Logic (FL) to control the position of the cart and to balance the pendulum. The proposed controllers are expected to have a simple design method and achieved high performances.