Energy Analysis for Air Conditioning System Using Fuzzy Logic Controller

 Reducing energy consumption and to ensure thermal comfort are two important considerations for the designing an air conditioning system. An alternative approach to reduce energy consumption proposed in this study is to use a variable speed compressor. The control strategy will be proposed using the fuzzy logic controller (FLC). FLC was developed to imitate the performance of human expert operators by encoding their knowledge in the form of linguistic rules. The system is installed on a thermal environmental room with a data acquisition system to monitor the temperature of the room, coefficient of performance (COP), energy consumption and energy saving. The measurements taken during the two hour experimental periods at 5-minutes interval times for temperature setpoints of 20oC, 22oC and 24oC with internal heat loads 0, 500, 700 and 1000 W. The experimental results indicate that the proposed technique can save energy in comparison with On/Off and proportional-integral-derivative (PID) control

Engine Speed Control using Online ANN for Vehicle with EMDAP-CVT

Controlling engine speed corresponding to load variations and road condition has always been a challenge to automotive engineers. However, with the introduction of Electro-Mechanical Dual Acting Pulley Continuously Variable Transmission (EMDAP-CVT),maintaining constant engine speed based on either its optimum control line or maximum engine power characteristic could be made possible. This paper describes the simulation work in this area carried out by the Drivetrain Research Group at the Automotive Development Centre, Universiti Teknologi Malaysia, Skudai Johor. The developed drive train model is highly non-linear; it could not be controlled satisfactorily by common linear control strategy such as PID controller. To overcome the problem, the use of Artificial Neural Network (ANN) is employed to indirectly control the engine speed by adjusting pulley CVT ratio. Computer simulations showed that applying artificial neural network (ANN) into drive train model could select a proper transmission ratio where the engine could be maintained to run at certain desired engine speed

Robust Motion Control for Mobile Manipulator Using Resolved Acceleration and Proportional-Integral Active Force Control

A resolved acceleration control (RAC) and proportional-integral active force control (PIAFC) is proposed as an approach for the robust motion control of a mobile manipulator (MM) comprising a differentially driven wheeled mobile platform with a two-link planar arm mounted on top of the platform. The study emphasizes on the integrated kinematic and dynamic control strategy in which the RAC is used to manipulate the kinematic component while the PIAFC is implemented to compensate the dynamic effects including the bounded known/unknown disturbances and uncertainties. The effectivenss and robustness of the proposed scheme are investigated through a rigorous simulation study and later complemented with experimental results obtained through a number of experiments performed on a fully developed working prototype in a laboratory environment. A number of disturbances in the form of vibratory and impact forces are deliberately introduced into the system to evaluate the system performances. The investigation clearly demonstrates the extreme robustness feature of the proposed control scheme compared to other systems considered in the study

Peleraian Buah Sawit dari Tandan Menggunakan Kaedah Kimia

A study was conducted on the effectiveness of a chemical substance, ethephon, on the 100 ening of oil palm fruit lets. Factors considered in the study were storage period, degree of ripeness, region and layer of spikelets within the oil palm bunch. Ethephon was poured into the stalk through a hole made using an electrical auger. The results obtained were analysed statistically using ANOVA and showed that the loosening of oil palm fruitlets was affected significantly by storage period, degree of ripeness and layer of spikelets within the bunch, but not by the region of spikelets

Introduction to control engineering

This book is intended to serve as a text book for a first course in control system engineering in higher institutes and universities. The text has been written through the experience of the authors in teaching this subject. Control systems are found in a broad range of applications within various engineering disciplines namely electrical, mechanical, chemical or aerospace engineerings. This book emphasizes particularly on the principle, design and analysis of feedback control system. The contents have been written to be suitable for all branches of engineering

Adaptive Pid Control With Pitch Moment Rejection For Reducing Unwanted Vehicle Motion In Longitudinal Directionle

This manuscript provides a detailed derivation of a full vehicle model, which may be used to simulate the behavior of a vehicle in longitudinal direction. The dynamics of a 14 degrees of freedom (14-DOF) vehicle model are derived and integrated with an analytical tire dynamics namely Calspan tire model. The full vehicle model is then validated experimentally with an instrumented experimental vehicle based on the driver input from brake or throttle pedals. Several transient handling tests are performed, namely sudden acceleration and sudden braking test. Comparisons of the experimental result and model response with sudden braking and throttling imposed motion are made. The results of model validation show that the trends between simulation results and experimental data are almost similar with acceptable error. An adaptive PID control strategy is then developed on the validated full vehicle model to reduce unwanted vehicle motions during sudden braking and throttling maneuver. The results show that the proposed control structure is able to significantly improve the dynamic performance of the vehicle during sudden braking and sudden acceleration under various conditions. The proposed controller will be used to investigate the benefits of a pneumatically actuated active suspension system for reducing unwanted vehicle motion in longitudinal directio

Structure optimization of neural network for dynamic system modeling using multi-objective genetic algorithm

The problem of constructing an adequate and parsimonious neural network topology for modeling non-linear dynamic system is studied and investigated. Neural networks have been shown to perform function approximation and represent dynamic systems. The network structures are usually guessed or selected in accordance with the designer's prior knowledge. However, the multiplicity of the model parameters makes it troublesome to get an optimum structure. In this paper, an alternative algorithm based on a multi-objective optimization algorithm is proposed. The developed neural network model should fulfil two criteria or objectives namely good predictive accuracy and minimum model structure. The result shows that the proposed algorithm is able to identify simulated examples correctly, and identifies the adequate model for real process data based on a set of solutions called the Pareto optimal set, from which the best network can be selected

Development and verification of a 9-DOF armored vehicle model in the lateral and longitudinal directions

This manuscript presents the development of an armored vehicle model in lateral and longitudinal directions. A Nine Degree of Freedom (9-DOF) armored vehicle model was derived mathematically and integrated with an analytical tire dynamics known as Pacejka Magic Tire model. The armored vehicle model is developed using three main inputs of a vehicle system which are Pitman arm steering system, Powertrain system and also hydraulic assisted brake system. Several testings in lateral and longitudinal direction are performed such as double lane change, slalom, step steer and sudden acceleration and sudden braking to verify the vehicle model. The armored vehicle model is verified using validated software, CarSim, using HMMWV vehicle model as a benchmark. The verification responses show that the developed armored vehicle model can be used for both lateral and longitudinal direction analysis

Position Tracking Of Slider Crank Mechanism Using Pid Controller Optimized By Ziegler Nichol’s Method

This paper presents a study on the position tracking response of a Propotional-Integral-Derivative (PID) controlled- slider crank mechanism, which is driven by a two phase stepper motor. In this study, the rod and crank are assumed to be rigid where the Newton second law is applied to formulate the equation of motion. A position tracking control of the slider crank mechanism is then developed by using PID controller. Several tests such as saw tooth, step function and square function are used in order to examine the performance of the proposed control structure. The results show that, the proposed control structure is able to tracking the desired position with a good response. The slider crank mechanism rig is then developed to investigate experimentally the ability of the proposed controller structure. The results show that the proposed control structure is able to track the desired displacements with accepTABLE error