×
The submission system is temporarily under maintenance. Please send your manuscripts to
Go to Editorial ManagerThe purpose of this research is to control a quarter car suspension system and also to reduce the fluctuated movement caused by passing the vehicle over road bump using modified PID (Proportional Integral and Derivative) controller. The proposed controller deals with dual loop feedback signals instead of single feedback signal as in the conventional PID controller. The structure of the modified PID controller was created by moving the proportional and derivative actions in the feedback path while remaining the integral action in the forward path. Thus, high accuracy results were obtained. Firstly, modelling and simulation of linear passive suspension system for a quarter car system was performed using Matlab – Simulink software. Then the linear suspension system was activated and simulated by using an active hydraulic actuator to generate the necessary force which can be regulated and controlled by the proposed controller. The performance of whole system has been enhanced with a modified PID controller.
This study uses intelligent techniques to regulate brushless direct current speed (BLDC) motors. After these motors solved the problem of using brushes and commutators in traditional DC motors, they succeeded in replacing brushes and commutators with electronic commutators. Due to the use of electronic switching, brushless motor algorithms are more complex than those of conventional motors. In this study, to adjust the PID controller's settings (Kp, Ki, and Kd), a trial-and-error approach was taken, and a completely new method known as the settings of known PID controllers have been modified using the new Gray Wolf algorithm. A BLDC motor's main benefit is that it has easy speed adjustment across a broad range, whereas AC motors often cannot be controlled in this way. Through the use of Matlab/Simulink, the BLDC motor's mathematical model was developed and implemented. The simulation results show that in the first case, a PID controller effectively induces the turbulent dynamic behavior of BLDC under load and no-load conditions, and in the second case, the speed shows the lowest rise time, stability, overshoot, and stability conditions, and performs at its best. The characteristics of the traditional PID controller that regulates the engine speed must be regulated online to achieve the use of intelligent technologies, and the adjustment is done online using the neural network. The results showed that this technology, or feature - online tuning - is the most effective and reliable of all.
This paper deals with the modeling and control strategics of the motion of wheeled mobile robot. The model of the mobile robot has two driving wheels and the azimuth and velocity are dependently controlled by two PID controllers. The PID controller is one of the earliest and famous industrial controllers. It has many advantages: It is economic, simple easy to be tuned and robu.~t. The tuning of these controllers is governed by system nonlinearities and continuous parameter variations. lbis paper deals with the optimal design of a PID controller for path tracking of mobile robot by using genetic algorithms (GA). The designed controller is tested for different paths.
This paper considers the neural network based PID controller. The learning and generalization properties of neural network are utilized in improving the performance of a conventional PID controller. Two different schemes are introduced. Both schemes are studied and their performances are comparatively evaluated on an example for uncertain system.
Over the past years, researchers have been focusing on development the robotics and actuation due to increase demand for these applications like industrial engineering, oil industry, healthcare, aerospace … etc. This work involves the design, construction and control of the Shape Memory Alloy (SMA) actuator. The industrial actuator has many characteristics able to be measured, which have an impact on the efficiency and effectiveness of the actuator while the execution of its tasks. The most important measurable characteristics are repeatability and accuracy. The current system typically is using Nitinol (Nickle Titanium Naval Ordinance Lab), which is one of the Shape Memory Alloy that contract when applying specific heat on it, and it can be used as an actuator. This work presents SMA in the shape of a spring to operate and control the accurate position of the 2-D system which containing four SMA springs, two SMA springs for the x -axis and two SMA springs for the y - axis. The theoretical design and calculations for SMA springs have been presented to collect information about the SMA springs. In a practical manner, the SMA spring characteristic like force and displacement were collected by a test bed that was designed and constructs before making the final rig. The setting shape of the SMA spring was presented and done as per the theoretical calculations. In the rig, each axis works as a two-direction actuator, the actuator is not prone to precise position points due to hysteresis and temperature variation. The SMA spring exhibited hysteresis and imprecise pointing, for that employing PID (Proportional Integral Derivative) with tracking mode controller to compensate the hysteresis. PID control system is played a decisive role with tracking mode model that achieves the aim behind the construction of the experimental rig. Good results have been obtained presented in three cases of drawing different shapes.
In this paper, a second order Sliding Mode Controller (SMC), based on Super – Twisting algorithm, Fuzzy estimator and PID controller is presented for quarter vehicle active suspensions. Because of the chattering that appeared at the output of the system when using first order SMC, second order SMC is preferred. The proposed controller has been derived in order to achieve the convergence and the stability of the system that can improve the comfortable driving and vehicles safety against different road disturbances. The Artificial Bee Colony optimization method has been utilized to find the optimal values of the proposed controller parameters. The obtained results of the simulations have been verified the efficiency and the ability of the proposed control scheme to suppress the oscillations and give the stability of the suspension system in the presence of uncertainty and different road disturbances.
The Mobile Manipulator Robot (MMR) has many applications in different aspects of the life, for example, grasping and transporting, mining, military, manufacturing, construction and others. The benefits of MMR rise in dangerous place where the human cannot reach such as disaster areas and dangerous projects sites. In this work, the PID controller is combined with Fuzzy Logic Controller (FLC) to structure the Fuzzy Supervisory Controller (FSC) to overcome the drawbacks of PID controller and to obtain the advantages of FLC. Two approaches are suggested for the navigation of Autonomous Mobile Robot (AMR). These are; goal reaching fuzzy control (GRFC) and the obstacle avoidance fuzzy control (OAFC). The hardware implementation of the AMR is performed using AVR ATmega32 microcontroller, two DC motors, light dependent resistor (LDR) and five Infra Red sensors. While, the Laboratory robot arm with some fabrications is used as manipulator arm with a five degrees-of- freedom. Then a microcontroller is employed to implement the proposed controller for MMR. The designed MMR is tested in real environments and give a good navigation.
This study presents a speed control design for switched reluctance motor (SRM) drive based on PID controller. The applications of Switched Reluctance Motors (SRMs) have being increased day by day, but this type of motors represents a highly nonlinear system, therefore there are a lot of difficulties in modeling and controlling them. We have proposed a non-linear mathematical model of a four phases 8/6 poles SRM then simulated it through Simulink/Matlab facilities. The whole control mechanism consists of a hysteresis current controller to minimize the torque ripple and a PID speed controller. The control design results are then validated in real-time by Simulink/Matlab software package.
Vehicles usually consist of several essential systems. The performance of the vehicle is evaluated through the efficiency of these systems to perform their duties. The suspension system is one of these systems dedicated to absorbing shocks arising from vehicles passing over road bumps, thus reducing vibrations and achieving passenger comfort while driving. This paper presents a study on enhancing ride comfort in a nonlinear half-car model using a modified Proportional-Integral-Derivative (PID) controller. In this study a half-car model is developed considering the nonlinearities in the suspension system components. A nonlinear half-car model was adopted to increase accuracy and make the overall system closer to reality. Instead of the feed-forward conventional PID controller gains, the proposed controller gains are formed by putting the proportional and derivative gains in the feedback path while keeping the integral gain in the feed-forward path to act as an I- PD controller. The proposed controller is integrated into the model to deal with these nonlinearities effectively and to achieve the optimal performance of the vehicle body. The overall system has been developed and simulated in the Matlab Simulink environment to show the dynamic response. Simulation results demonstrate the effectiveness of the I-PD controller in improving the ride comfort and handling stability of the nonlinear half-car model by reducing body acceleration and suspension deflection. A comparison with other study has been conducted to verify the effectiveness of the proposed controller.
In this paper a combining Neurofuzzy and PID controllers have been employed for controlling the positions and rotational motions of the mini-helicopter system. Due to the strong coupling between the state variables of the mini-helicopter model, therefore, it is not suitable to design single controller for regulating the positions and rotational motions of the given model. To solve this problem, three neurofuzzy controllers are designed for the lateral, longitudinal and heave motion; and three classical PID controllers are proposed for attitude control. Nine rules are suggested for each neurofuzzy network depends on the previous knowledge/experiences of expert human pilot. The simulation results show that the proposed controllers are very effective to control the hovering, position and forward flight of the mini-helicopter system.
Obstacle avoidance and path planning are from the most important problems in mobile robots, especially in unknown environment . In this paper, we proposed an approach for mobile robot navigation combining path planning and obstacle avoidance. Methods such as obstacle avoidance are inspired from the nature, and have been developed by fuzzy logic to train an intelligent robot in unknown environment. The model of the robot has two driving wheels and the linear velocity and azimuth of the two wheels are independently controlled using PID controller. Inputs are obtained from ultrasonic sensors mounted on it.