Mohd. Zarhamdy Md. Zain

A nonparametric approach using artificial intelligence in vibration and noise reduction of flexible systems

The main aim of this paper is to broaden the application’s area of artificial intelligence including fuzzy logic and multiobjective evolutionary algorithm into real-time control area. Wiper system is a high order, nonlinear model with single-input and multi-outputs so that rise time, maximum overshoot, and end-point vibration of wiper blade are observed in conflict as the faster response leads to the larger level of undesired noise and vibration. The first part of this paper centers acquiring experimental data from a passenger automobile wiper system during its operation and using a reliable nonlinear system identification, namely, nonlinear autoregressive exogenous Elman neural network. Knowing that in a practical environment, where the loading conditions of the flexible wiper blade may be varied due to rain, snow, or wind lift in high-speed driving, causing changes in the characteristics of the system, the system performance with a fixed conventional controller scheme will not be satisfactory. The main contribution of this work is presented in second part where a novel multiobjective, bilevel adaptive-fuzzy controller is proposed for an automobile wiper system. The system’s parameters are tuned simultaneously by a multiobjective genetic algorithm based on fitness sharing whereby an automobile wiper blade is moved within its sweep workspace in the least amount of time with minimum noise and vibration.

Practical multi-objective controller for preventing noise and vibration in an automobile wiper system

This paper presents an approach using a multi-objective controller to prevent noise and vibration generated by the wiper blade during its wiping operation. Firstly, this paper focuses on the experimental approach to collect noise and vibration data from a car wiper system during its operation and secondly, to develop black box model of the wiper system using nonparametric approach of system identification known as nonlinear auto regressive exogenous Elman neural network (NARXENN). Finally, a novel closed loop iterative input shaping controller whose parameters are tuned simultaneously by a Pareto based multi objective genetic algorithm (MOGA) are proposed and simulated in such a way that it can prevent unwanted noise and vibration in the wiper system. The main contribution of this work rather the previous studies of automobile wiper system is to develop a novel multi-objective control strategy whereby an automobile wiper blade is moved within its sweep workspace in the least amount of time with minimum noise and vibration.

Hybrid learning control for improving suppression of hand tremor

Patients with hand tremors may find routine activities such as writing and holding objects affected. In response to this problem, an active control technique has been examined in order to lessen the severity of tremors. In this article, an online method of a hybrid proportional–integral control with active force control strategy for tremor attenuation is presented. An intelligent mechanism using iterative learning control is incorporated into the active force control loop to approximate the estimation mass parameter. Experiments were conducted on a dummy hand model placed horizontally in a tremor test rig. When activated by a shaker in the vertical direction, this resembles a postural tremor condition. In the proportional–integral plus active force control, a linear voice coil actuator is used as the main active tremor suppressive element. A sensitivity analysis is presented to investigate the robustness of the proposed controller in a real-time control environment. The findings of this study demonstrate that the intelligent active force control and iterative learning controller show excellent performance in reducing tremor error compared to classic pure proportional, proportional–integral and hybrid proportional–integral plus active force control controllers.

Active Force Control of a fluidic muscle system using Fuzzy Logic

In this paper, Active Force Control with Fuzzy Logic (AFCFL) technique is applied to the control of a fluidic muscle (also known as pneumatic artificial muscle or PAM) that acts as an actuator to drive a trolley system in a laboratory setting. Since, fluidic muscle has a high-tension force, high power/weight ratio, high strength, and cleanliness, ease of maintenance, low cost, compactness and cheap power source, it has caught the attention of researchers in the area of robotics. Despite of its advantageous, the presence of the inherent high nonlinearity behaviour, high hysteresis and time variance in the system has made it a challenging and interesting system for modelling and control design. The main goal of this study is to perform accurate position control of a trolley through a hardware-in-the-loop simulation (HILS) implementation so as to enhance the system performance through the AFCFL scheme. Experimental results demonstrate the effectiveness and robustness of the proposed controller compared to the conventional proportional-integral-derivative (PID) control method.

Development of experimental-rig for human postural tremor behaviour

The purpose of this study is to investigate the human hand tremor behaviour in postural condition considering experimental works performed on actual human hand and a developed rig which was specifically designed to induce vibration in an intra vernacular training (IVT) hand-arm model. Two DC motors were used to spin unbalanced masses as the source of excitation to the model. Thus, this produces vibration along the hand-arm model to emulate the behaviour of postural tremor phenomenon. The quantitative assessment of tremor of the hand-arm model was mainly measured and recorded using a light-weight accelerometer and a displacement laser sensor. The accelerometer converts the physical movement into acceleration signals while the laser displacement sensor was used for precise measurement due to their high sensitivity in motion. The latter transducer was directly targeted at the palm of the hand, adjacent to the location of the accelerometer. The displacement and acceleration signals were then examined in both time and frequency domains. The results from the experiment and simulation study can be used for further analysis of human hand-arm tremor (of typically a PD patient) and the development of anti-human arm tremor device that can eventually suppress the tremor.

Dynamic Analysis on Noise and Vibration Study of Flexible Wiper Blade System

Chatter is one of the unwanted noise and vibration phenomenon which are generated during the wiper operation. It is a low frequency and self-excited vibration that is often generated before and after the wiper reverses its direction. This leads to a poor visibility and annoying sound to the driver and passengers. Therefore, this paper is aimed to propose a technique that can be apply to tackle this problem. Hence, an existing two-dimensional mathematical model of a wiper system available in the open literature is adopted. Firstly, the baseline model is simulated in order to observe its vibration response. Then, an input shaping control scheme is introduced into the baseline model. It is found that the input shaping control scheme can reduce the vibration level approximately by 30 percents from the baseline model.

Effect of transducer mass on thin plate vibration

Transducer attached to a structure during vibration testing is a direct addition of mass especially when the structure itself is relatively light. This paper present result from a study on the effect of transducer mass on thin plate vibration. A rectangular thin plate of mild steel was used as the test structure. The influence of the transducer mass on the natural frequencies and the mode shapes of the thin plate were investigated. Numerical analysis and experimental modal analysis were conducted on the test structure to obtain the natural frequencies and mode shapes for the first 3000 Hz. The numerical analysis was conducted using MSC Nastran finite element analysis software. Normal Modes Analysis and impact testing were conducted to obtain the natural frequencies and the corresponding mode shapes of the thin plate. The resulting natural frequencies were tabulated and mode shapes comparisons from the simulations are presented in contour plots.

Tremor suppression for 4-DOFs biodynamic hand model using genetic algorithm

A person who has severe hand tremor will have difficulty in doing specific tasks such as eating, combing or holding any objects. Currently, there is no medication that can cure the tremor. Thus, this study proposes the active tremor control, in which an intelligent controller is applied to suppress the hand tremor. The main objective is to optimise the proportional-integral (PI) controller using genetic algorithm (GA). A linear voice coil actuator (LVCA) is applied onto a four degree of freedom (4-DOF) human hand model represented in state space. The findings of the study demonstrate that the PI controller optimised by GA gives excellent performance in reducing the tremor error. Based on the frequency evaluation, the PI controller performance was roughly around 84% in reducing the peak of simulated hand tremor. The outcomes provide an important contribution towards achieving novel methods in suppressing hand tremor model by means of intelligent control.

Semi-active suspension control for formula SAE car using magneto-rheological fluid

The Magneto-rheological (MR) fluid damper is prevalent in the field of semi-active suspension whose viscosity changes by the change of magnetic field passing through the damping fluid. In this study, a semi-active suspension quarter car model is employed as a plant. The Bingham model of MRF damper is exploited with PID and Fuzzy + PID controllers. The current is controlled by the controllers according to the quarter car chassis disturbance. The step road profile is used as an input disturbance to the suspension system. The displacement of sprung mass is analyzed in terms of time and frequency domain. The maximum power spectral density of acceleration for step response with Fuzzy + PID is reduced by 87.28 % as compared to passive suspension whereas PID reduced only 79.95 %. This indicates that the MRF damper with right tuned Fuzzy + PID controller provide a safer ride compared to PID controller and passive suspension.

Periodic Cubic Spline on Motion of Five-Link Human Bipedal Model Using Nonlinear Predictive Control

This paper studies about the performance of periodic cubic spline applied on the nonlinear predictive control (NPC) based on receding-horizon cost function optimization. The five-link human bipedal model includes a torso and two legs which has a thigh and a shank in every leg. The periodic cubic spline is used to achieve smooth walking trajectories of every joint in the bipedal model in the sagittal plane. The results show that the tracking error after using periodic cubic spline is smaller than the tracking error before using periodic cubic spline.