Simulation of a Self-Balancing Platform on the Mobile Car

In the last years, the self-balancing platform has become one of the most common candidates to use in many applications such as flight, biomedical fields, industry. This paper introduced the simulated model of a proposed self-balancing platform that described the self–balancing attitude in (X-axis, Y-axis, or both axis) under the influence of road disturbance. To simulate the self-balanced platform's performance during the tilt, an integration between Solidworks, Simscape, and Simulink toolboxes in MATLAB was used. The platform's dynamic model was drawn in SolidWorks and exported as a STEP file used in the Simscape Multibody environment. The system is controlled using the proportional-integral-derivative (PID) controller to maintain the platform leveled and compensate for any road disturbances. Several road disturbances scenarios were designed in the x-axis, y-axis, or both axis (the pitch and roll angles) to examine the controller effectiveness. The simulation results indicate that that the platform completed self-balancing under the effect of disturbance (10° and -10°) on the X-axis, Y-axis, and both axes in less than two milliseconds. Therefore, a proposed self-balancing platform's simulated model has a high self-balancing accuracy and meets operational requirements despite its simple design.

New Tuning Approach of Fuzzy Logic System Using Proportional Integral Observer for Tracking a Nonlinear System

Proportional integral observer (PIO) for tracking a nonlinear method has a lower sentiency to cipher the state and output variables. So a more nonlinear controller has to be else to control to activity. In this paper, a fuzzy logic (FLC) controller has been added to the PIO to meliorate the calculation transmute. A fuzzy proportional integral observer (FPIO) for following a nonlinear system has been premeditated to decimate the susceptibleness to cipher the tell and turnout variables with the existent posit and product variables. The FPIO controller has been tested for improving the estimation control using a nonlinear quarter vehicle active suspension system with a nonlinear hydraulic actuator. A comparison simulation of the proposed nonlinear system for estimating the state variables and tracking the output (suspension deflection) with a set point bump road disturbance using FPIO and PIO. The comparison simulation result shows that the estimated state variables and system output match the actual ones perfectly using a fuzzy PIO controller.

Regeneration Energy for Nonlinear Active Suspension System Using Electromagnetic Actuator

The main purpose of using the suspension system in vehicles is to prevent the road disturbance from being transmitted to the passengers. Therefore, a precise controller should be designed to improve the performances of suspension system. This paper presents a modeling and control of the nonlinear full vehicle active suspension system with passenger seat utilizing Fuzzy Model Reference Learning Control (FMRLC) technique. The components of the suspension system are: damper, spring and actuator, all of those components have nonlinear behavior, so that, nonlinear forces that are generated by those components should be taken into account when designed the control system. The designed controller consumes high power so that when the control system is used, the vehicle will consume high amount of fuel. It notes that, when vehicle is driven on a rough road; there will be a shock between the sprung mass and the unsprung mass. This mechanical power dissipates and converts into heat power by a damper. In this paper, the wasted power has reclaimed in a proper way by using electromagnetic actuator. The electromagnetic actuator converts the mechanical power into electrical power which can be used to drive the control system. Therefore, overall power consumption demand for the vehicle can be reduced. When the electromagnetic actuator is used three main advantages can be obtained: firstly, fuel consumption by the vehicle is decreased, secondly, the harmful emission is decreases, therefore, our environment is protected, and thirdly, the performance of the suspension system is improved as shown in the obtained results.

Analytical and Experimental Evaluation of Various Active Suspension Alternatives for Superior Ride Comfort and Utilization of Autonomous Vehicles

Autonomous vehicles (AVs) give the driver opportunity to engage in productive or pleasure-related activities, which will increase AV’s utility and value. It is anticipated that many AVs will be equipped with active suspension extended with road disturbance preview capability to provide the necessary superior ride comfort resulting in almost steady work or play platform. This article deals with assessing the benefits of introducing various active suspensions and related linear quadratic regulator (LQR) controls in terms of improving the work/leisure ability. The study relies on high-performance shaker rig-based tests of a group of 44 drivers involved in reading/writing, drawing, and subjective ride comfort rating tasks. The test results indicate that there is a threshold of root-mean-square vertical acceleration, below which the task execution performance is similar to that corresponding to standstill conditions. For the given, relatively harsh road disturbance profile, only the fully active suspension with road preview control can suppress the vertical acceleration below the above critical superior comfort threshold. However, when adding an active seat suspension, the range of chassis suspension types for superior ride comfort is substantially extended and can include semi-active suspension and even passive suspension in some extreme cases that can, however, lead to excessive relative motion between the seat and the vehicle floor. The design requirements gained through simulation analysis, and extended with cost and packaging requirements related to passenger car applications, have guided design of two active seat suspension concepts applicable to the shaker rig and production vehicles.

Predictive Control Using Active Aerodynamic Surfaces to Improve Ride Quality of a Vehicle

This work presents a predictive control strategy for a four degrees of freedom (DOF) half-car model in the presence of active aerodynamic surfaces. The proposed control strategy consists of two parts: the feedback control deals with the tracking error while the feedforward control handles the anticipated road disturbance and ensures the desired maneuvering. The desired roll and pitch angles are obtained by using disturbance, vehicle speed and radius of curvature. The proposed approach helps the vehicle to achieve better ride comfort by suppressing the amplitude of vibrations occurring in the vertical motion of the vehicle body, and enhances the road-holding capability by overcoming the amplitude of vibrations in tyre deflection. The control strategy also cancels out the hypothetical forces acting on the vehicle body to help the vehicle to track the desired attitude motion without compromising the ride comfort and road-holding capability. The simulations results show that the proposed control strategy successfully reduces the root mean square error (RMSE) values of sprung mass acceleration as well as tyre deflection.

Apply a Fuzzy Algorithm to Control an Active Suspension in a Quarter Car by Matlab’s Simulink

This paper presents modeling and simulation of spring-mass damper system for quarter car in the Simulink environment. The simulations in this research have been carried out by using the Simulink of Matlab. The parameters in the simulation model for the suspension system under study include car body mass, wheel mass, spring and damping elements of shock absorber, and tire. A road disturbance profile comprising a combination of two sinusoidal curves is modeled. Controllers that are used in this study are the proposed fuzzy logic controller. The purpose of this research is to improve vehicle comfort using the Fuzzy Logic Controller (FLC). The simulation results of the system perform well fulfill the minimum percentage requirements and fast stability time, provide good leveling of stability and ride comfort.

Nonlinear Control Design of a Half-Car Model Using Feedback Linearization and an LQR Controller

Effective control of ride quality and handling performance are challenges for active vehicle suspension systems, particularly for off-road applications. The nonlinearities tend to degrade the performance of active suspension systems; these introduce harshness to the ride quality and reduce off-road mobility. Typical control strategies rely on linear models of the suspension dynamics. While these models are convenient, nominally accurate, and controllable due to the abundance of linear control techniques, they neglect the nonlinearities present in real suspension systems. The techniques already implemented and methods used to cope with problem of Half-Car model were studied. Every method and technique had some drawbacks in terms of complexity, cost-effectiveness, and ease of real time implementation. In this paper, an improved control method for Half-Car model was proposed. First, input/output feedback linearization was performed to convert the nonlinear system of Half-Car model into an equivalent linear system. This was followed by a Linear Quadratic Regulator (LQR) controller. This controller had minimized the effects of road disturbances by designing a gain matrix with optimal robustness properties. The proposed control technique was applied in the presence of the deterministic road disturbance. The results were verified using the Matlab/Simulink toolbox.