Musa Mailah

SIMULATION OF A SUSPENSION SYSTEM WITH ADAPTIVE FUZZY ACTIVE FORCE CONTROL

This paper presents the design of a new and novel control technique applied to an active suspension system of a quarter car model using adaptive fuzzy (AF) logic and active force control (AFC) strategies. The two main advantages of the proposed method are the simplicity of the control law and low computational burden. The overall control system essentially comprises three feedback control loops, namely the innermost PI control loop for the force tracking of the hydraulic actuator, intermediate AFC control loops for the compensation of the disturbances and outermost AF control loop for the computation of the optimum target/commanded force. AF algorithms were used to approximate the estimated mass of the hydraulic actuator in the AFC loop. The performance of the proposed control method was then simulated, evaluated and later compared to examine the effectiveness of the system in suppressing the undesirable effects of the suspension system. It was found that the active suspension system with Adaptive Fuzzy Active Force Control (AF-AFC) yields superior performance compared to the AF system without AFC and the passive counterparts.

Genetic algorithm-based identification of transfer function parameters for a rectangular flexible plate system

This paper focuses on an identification technique based on genetic algorithms (GAs) with application to rectangular flexible plate systems for active vibration control. A real coded GA with a new truncation-based selection strategy of individuals is developed, to allow fast convergence to the global optimum. A simulation environment characterizing the dynamic behavior of a flexible rectangular plate system is developed using the central finite difference (FD) techniques. The plate thus developed is excited by a uniformly distributed random disturbance and the input-output data of the system acquired is used for black-box modeling the system with the GA optimization using an autoregressive model structure. Model validity tests based on statistical measures and output prediction are carried out. The prediction capability of the model is further examined with unseen data. It is demonstrated that the GA gives faster convergence to an optimum solution and the model obtained characterizes the dynamic system behavior of the system well.

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.

Self-learning active vibration control of a flexible plate structure with piezoelectric actuator

Abstract In this paper, an active vibration control (AVC) incorporating active piezoelectric actuator and self-learning control for a flexible plate structure is presented. The flexible plate system is first modelled and simulated via a finite difference (FD) method. Then, the validity of the obtained model is investigated by comparing the plate natural frequencies predicted by the model with the reported values obtained from literature. After validating the model, a proportional or P-type iterative learning (IL) algorithm combined with a feedback controller is applied to the plate dynamics via the FD simulation platform. The algorithms were then coded in MATLAB to evaluate the performance of the control system. An optimized value of the learning parameter and an appropriate stopping criterion for the IL algorithm were also proposed. Different types of disturbances were employed to excite the plate system at different excitation points and the controller ability to attenuate the vibration of observation point was investigated. The simulation results clearly demonstrate an effective vibration suppression capability that can be achieved using piezoelectric actuator with the incorporated self-learning feedback controller.

Active Force with Fuzzy Logic Control of a Two-Link Arm Driven by Pneumatic Artificial Muscles

In this paper, the practicality and feasibility of Active Force Control (AFC) integrated with Fuzzy Logic(AFCAFL) applied to a two link planar arm actuated by a pair of Pneumatic Artificial Muscle (PAM) is investigated. The study emphasizes on the application and control of PAM actuators which may be considered as the new generation of actuators comprising fluidic muscle that has high-tension force, high power to weight ratio and high strength in spite of its drawbacks in the form of high nonlinearity behaviour, high hysteresis and time varying parameters. Fuzzy Logic (FL) is used as a technique to estimate the best value of the inertia matrix of robot arm essential for the AFC mechanism that is complemented with a conventional Proportional-Integral-Derivative (PID) control at the outermost loop. A simulation study was first performed followed by an experimental investigation for validation. The experimental study was based on the independent joint tracking control and coordinated motion control of the arm in Cartesian or task space. In the former, the PAM actuated arm is commanded to track the prescribed trajectories due to harmonic excitations at the joints for a given frequency, whereas for the latter, two sets of trajectories with different loadings were considered. A practical rig utilizing a Hardware-In-The-Loop Simulation (HILS) configuration was developed and a number of experiments were carried out. The results of the experiment and the simulation works were in good agreement, which verified the effectiveness and robustness of the proposed AFCAFL scheme actuated by PAM.

A PC-based driving simulator using virtual reality technology

Driving simulators are frequently used for vehicle system development, human factor study, and vehicle safety research by enabling the reproduction of the actual driving environments in a safe and tightly controlled environment. Recent development of powerful desktop computer workstations can now support the computational requirement of small to medium-scale driving simulators. The driving simulator for this research is developed using PC-based workstations that are capable of producing high fidelity graphics at reasonable cost. The VR-based simulator gives a driver on board the impression that he drives an actual vehicle by predicting vehicle motion caused by the driver input and feeding back the corresponding visual, motion, audio and proprioceptive cues to the driver. This research is intended to provide a test bed for simulating driving related task using virtual reality technology.

Experimental study of human hand-arm model response

This paper describes the development of a hand-arm model rig to represent the behavior of human postural tremor. The experimental rig is designed as an apparatus to induce vibration along the hand-arm model. In this study an Intra Vernacular (IV) Training arm is used as the hand-arm model. Two DC motors are used each driving an unbalancing mass to produce vibration along the arm model which is very similar to the human postural tremor behaviour. In this experimental work, three different frequencies are used for analysis. Displacement and acceleration dynamic responses of a selected point on the hand model are captured and recorded using a light-weight accelerometer mounted on a glove. The data can be used for further analysis of the human hand-arm tremor especially for Parkinsons disease (PD) patients. Results from the experiment are considered raw data which can later be used to assist in the design of appropriate instruments or devices that can suppress the hand tremor vibration.

Active force control of 3-RRR planar parallel manipulator

This paper presents a new and novel method to control a 3-RRR (revolute-revolute-revolute) planar parallel manipulator using an active force control (AFC) strategy. A traditional proportional-integral-derivative (PID) controller was first designed and developed to demonstrate the basic and stable response of the manipulator in performing trajectory tracking tasks. Later, the AFC section was incorporated into the control scheme in cascade form by adding it in series with the PID controller (PID+AFC), its primary aim of which is to improve the overall system dynamic performance particularly when the manipulator is subjected to different loading conditions. Results clearly illustrate the robustness and effectiveness of the proposed AFC-based scheme in rejecting the disturbances compared to the traditional PID controller.

Active Force Control Applied to Spray Boom Structure

Distribution pattern of spray boom in fields is affected by several parameters which one of the important reasons is horizontal and vertical vibrations because of unevenness surfaces. Spray boom movements lead to decrease of spread efficiency and crop yield. Generally, active suspension is employed to control and attenuate the vibration of sprayer booms because these suspensions reduce the high frequency vibration of spray booms thanks to irregularities soil. In this research, a proportional-integral-derivative controller with active force control is used to remove undesired rolling of spray boom. Simulation results depict that the proposed scheme is more effective and accurate than PID control only scheme. The AFC based scheme shows the robustness and accuracy compared to the PID controller.

Roll Movement Control of a Spray Boom Structure Using Active Force Control with Artificial Neural Network Strategy

Currently, most of modern sprayers are equipped with suspensions for improving the uniformity of spray application in the field. Therefore, this paper represents the possibility of applying active force control (AFC) technique for the control of a spray boom structure undesired roll movement through a simulation analysis. The dynamic model of the spray boom was firstly defined and an AFC-based scheme controller was designed and simulated in MATLAB environment. Artificial neural network (ANN) is incorporated into the AFC scheme to tune the proportional-derivative (PD) controller gains andcompute the spray boom estimated mass moment of inertia. The training of both ANN with multi layer feed forward structure was done using Levenberg-Marquardt (LM) learning algorithm. To evaluate the AFC-ANN control system robustness, various types of disturbances and farmland terrain profileshave been used to excite the spray boom. The results of the study demonstrated that the AFC-based method offers a simple and effective computation compared to the conventional proportional-integral-derivative (PID) control technique in attenuating the unwanted spray boom roll oscillation or vibration. The AFC-ANN scheme is found to exhibit superior performance for different proposed terrain profilesin comparison to the AFC-PD and pure PD counterparts.