Hazlina Selamat

Nonlinear Identification of a Magneto-Rheological Damper Based on Dynamic Neural Networks

Semi-active control of dynamic response of civil structures with magneto-rheological (MR) fluid dampers has emerged as a novel revolutionary technology in recent years for designing “smart structures.” A small-scale MR damper model with the valve mode mechanism has been examined in this research using dynamic recurrent neural network modeling approach to reproduce its hysteretic nonlinear behavior. Modified Bouc–Wen model based on nonlinear differential equations has not only been employed as the reference model to provide a comprehensive training data for the neural network but also for comparison purposes. A novel frequency and amplitude varying displacement input signal (modulated chirp signal) associated with a random supply voltage has been introduced for persistent excitation of the damper in such a way to cover almost all of its operating conditions. Finally a series of validation tests were conducted on the proposed model which proved the appropriate performance of the model in terms of accuracy and capability for realization.

Intelligent Modeling and Control of a Conveyor Belt Grain Dryer Using a Simplified Type 2 Neuro-Fuzzy Controller

In this article, a nonlinear autoregressive with exogenous input (NARX) network was utilized to model a conveyor belt grain dryer using a set of input–output data collected during an experiment to dry paddy grains. The resulting NARX model has achieved a remarkable modeling accuracy compared to other previously reported modeling techniques. To control the considered dryer, a simplified type 2 adaptive neuro-fuzzy inference system (ANFIS) controller was proposed. The effectiveness of this controller was demonstrated by several performance tests conducted by computer simulations. Moreover, a comparative study with other related controllers further confirmed the superiority of the proposed dryer controller.

Yaw stability improvement for four-wheel active steering vehicle using sliding mode control

Active steering control is one of the approach that can be used to improve the vehicles lateral and yaw stability. By combining active front steering and active rear steering control, the vehicles handling and stability can be improved via four wheel active steering (4WAS) control. In this paper, a robust control algorithm of sliding mode control is designed for 4WAS vehicle. Single track 2 d.o.f linear model is utilized for controller design and simulation purpose. Simulation for 4WAS and front steering (AFS) is carried out in Simulink for step steer and double lane change maneuver to verify the effectiveness of the proposed control system. The result shows that the 4WAS perform better than the AFS in tracking the desired response trajectory.

PID controller optimization for a rotational inverted pendulum using genetic algorithm

Rotational inverted pendulum (RIP) is widely used as a benchmark system in evaluating various control strategies, as it is an ideal test bed that represents under-actuated plants. Although a proportional-integral-derivative (PID) controller is popular and relatively simple in structure, its use in balancing the RIP is usually not recommended due to the difficulties in finding the suitable PID controller parameter values for the RIP system, which has two unstable open-loop poles. Therefore, this paper presents an investigation on a PID tuning problem for stabilizing the RIP using a variant of multi-objective Genetic Algorithm (GA), called the Global Criterion Genetic Algorithm (GCGA). Simulation work has shown that GCGA is capable in tuning the PID controller gains to balance the RIP. Compared to the standard single objective GA, the solutions found in GCGA have better control performances. The optimization results have then been applied to the real RIP in order to validate the results in the real-time environment.

PFI System for Retrofitting Small 4-Stroke Gasoline Engines

Fuel injection system is a promising technology that enhances positively the fuel economy, engine performances and emission reduction, as compared to the conventional carburetor system. Currently, motorcycles using carburetor system are widely used as a mean of transportation especially in urban areas. This conventional fuelling system produces more harmful emissions and consumes more fuel compared to the fuel injection system. It is therefore desirable to have a fuel injection system that can easily be retrofitted to the current on-road motorcycles. This paper presents a review and comparative study using 1-D simulation software - GT-Power, on electronic fuel injection (EFI) system between port-fuel injection (PFI) and direct injection (GDI) system for retrofitment purpose of small 125cc 4-stroke gasoline engine. From this study, PFI system has been selected based on its high brake power, brake torque, and brake mean effective pressure with low brake specific fuel consumption.

Vehicle stability enhancement based on second order sliding mode control

The vehicle handling and stability in emergency situation can be enhanced with direct yaw moment control (DYC). In this paper, a new controller using super twisting technique based on second order sliding mode control (SOSM) is proposed for the yaw moment control. The controller is designed based on two degree of freedom (2DOF) nonlinear model. The effectiveness of the proposed controller is compared to PI controller and conventional sliding mode controller by co-simulations in CarSim and Matlab/Simulink. The results show that the SOSM give better performance in tracking the desired response necessary for the vehicle handling and stability. In addition, the chattering phenomenon is also reduced, giving a smooth tracking trajectory.

FPGA-Based Implementation of Kalman Filter for Real-Time Estimation of Tire Velocity and Acceleration

Antilock braking systems require accurate vehicle speed and acceleration estimations from wheel speed sensors. Adaptive Kalman filtering is used to estimate wheel speed and acceleration for each wheel. Single core or multicore processor-based embedded systems perform the required estimation using a two-stage extended Kalman filter in many clock cycles, which limits Kalman filter speed and accuracy. In the proposed system, purely arithmetic operations used in the process are simplified and implemented as embedded logic to reduce the overhead delays and increase the update rate by 48%. The proposed system is run sequentially using finite-state machines, while a large number of multiplication and division operations are removed through rewiring and logic reuse. The simplifications not only reduce the amount of logic required to perform the operations by 39.7% but also use simple logic, which can run faster than the replaced logic on field-programmable gate array. The results presented show comparable root-mean-square wheel speed error with a high update rate of 20 MHz when running on a 50-MHz board in all scenarios. The system also provides accurate wheel acceleration estimation, which is crucial for many systems, including the reference system.

Modelling of a conveyor-belt grain dryer utilizing a sigmoid network

Post-harvest techniques play an important role in modern agricultural industry. One of these essential post-harvest techniques is the grain drying process. However, this process is characterized by its high complexity and nonlinearity due to the effects of several drying parameters. Therefore, conventional modelling approaches cannot produce accurate modelling results to describe the dynamics of this challenging process. This paper presents a nonlinear modelling technique to develop a highly accurate model for a laboratory-scale conveyor-belt grain drying system. In particular, this modelling technique is based on utilizing the sigmoid network as a nonlinearity estimator in a nonlinear autoregressive with exogenous input (NARX) model. As the training samples, a set of experimental input-output data was used in the model development process. This data set was collected from the conveyor-belt grain dryer during a real-time experiment to dry paddy (rough rice) grains. Compared to other previously reported modelling techniques which were applied for the same drying process, the proposed sigmoid-based NARX model has achieved the best modelling accuracy in describing the grain drying process. More precisely, the proposed model has achieved a root mean squared error (RMSE) of 2.776 × 10-17. It is worth to highlight that, unlike previous efforts which aimed at modelling conveyor-belt grain drying systems, the advantage of the proposed modelling technique is that it can be directly applied to model the drying system regardless of the dryer shape, and moreover regardless of the size and physical properties of the grains to be dried. In addition, the resulting model can be readily employed in control applications to design suitable dryer controllers.

PFI retrofit-kit as green technology for small 4-stroke S.I. Engine

This paper presents outcomes of the usage of a developed prototype of PFI retrofit-kit for small 4-stroke gasoline engine. The developed PFI retrofit-kit produced good and high brake power and brake mean effective pressure compared to the carburetor system with over 50% improvement. Exhaust-out emissions such as carbon monoxide, carbon dioxide and hydrocarbon have been reduced in the range of 39%, 185%, and 57% respectively. However, brake specific fuel consumption was found to be higher (125%) as compared to carburetor system.

Electronic Control Unit Design for a Retrofit Fuel Injection System of a 4-Stroke 1-Cylinder Small Engine

Most motorcycles in developing countries use carburetor systems as the fuel delivery method especially for models with the cubic capacity of less than 125cc. However, small gasoline fuelled engines operating using carburetor system suffer from low operating efficiency, waste of fuel and produce higher level of hazardous emissions to the environment. In this study, an electronic control unit (ECU) is designed and simulated for a retrofit fuel injection (FIS) system. The ECU is targeted to have a simple design, reliable and offers all of the necessary functions of the modern ECU. The simulation results shows that the designed ECU can determine the injection period as close to the proposed value and can drive the injector efficiently based on the generated PWM pulse.