Analysis of Synchronous Moment for Active Front Steering and a Two Actuated Wheels of Electric Vehicle Based on Dynamic Stability Enhancement

2019 ◽  
Vol 11 (1) ◽  
Author(s):  
Eid. S. Mohamed ◽  
Mh.I. Khalil ◽  
Ahmed A.A. Saad
Keyword(s):  
Linear Quadratic Regulator ◽  
Vehicle Stability ◽  
Linear Quadratic ◽  
Smart Systems ◽  
Active Front Steering ◽  
Lqr Controller ◽  
Optimal Linear ◽  
Vehicle Trajectory ◽  
Stability Enhancement ◽  
Yaw Moment

Active Front Steering (AFS) and Direct Yaw moment Controller (DYC) are the vehicle smart systems to improve the vehicle stability and safety. The AFS uses front wheels Steer-By-Wire (SBW) system. DYC uses Rear Independent in Wheel Actuated Electric Vehicles (RIWA-EVs). It generates yaw moment to correct the vehicle state deviations. The proposed controller algorithm consists of two levels. First level feedback controller evaluate the optimal yaw moment generated to achieve the desired vehicle trajectory motion with minimize the yaw rate and side-slip errors. The second level controller is utilized to allocate the required front steer angle and traction/ regeneration to the RIWA embedded in rear wheels by taking into account the tire slip. An optimal Linear Quadratic Regulator (LQR) controller is designed, and its controller effectiveness is evaluated under various input driving manoeuvres. The results indicate that the integrated AFS/DYC can significantly stabilize the vehicle motion and highly reduce the driver’s workload. The laboratory experiment of AFS subsystem, for adequate actual front steering angle is measured, in order to apply in vehicle model to predict the responses. The results disclose that the RMS can be an effective route to monitor the vehicle stability.

Vehicle Dynamics Control Based on Linear Quadratic Regulator

2009 ◽  
Vol 16-19 ◽  
pp. 876-880
Author(s):  
Si Qi Zhang ◽  
Tian Xia Zhang ◽  
Shu Wen Zhou
Keyword(s):  
Control Strategy ◽  
Vehicle Dynamics ◽  
Linear Quadratic Regulator ◽  
Active Safety ◽  
Vehicle Stability ◽  
Steering Control ◽  
Linear Quadratic ◽  
Yaw Rate ◽  
Vehicle Dynamics Control ◽  
Yaw Moment

The paper presents a vehicle dynamics control strategy devoted to prevent vehicles from spinning and drifting out. With vehicle dynamics control system, counter braking are applied at individual wheels as needed to generate an additional yaw moment until steering control and vehicle stability were regained. The Linear Quadratic Regulator (LQR) theory was designed to produce demanded yaw moment according to the error between the measured yaw rate and desired yaw rate. The results indicate the proposed system can significantly improve vehicle stability for active safety.

Active Command-Steering Control of Tractor and Three Full Trailers for Tractor-Track Following

2006 ◽  
Author(s):  
Krishna Rangavajhula ◽  
H.-S. Jacob Tsao
Keyword(s):  
High Speed ◽  
Control Strategies ◽  
Linear Quadratic Regulator ◽  
Cost Effective ◽  
Steering Control ◽  
Linear Quadratic ◽  
Amplification Ratio ◽  
High Speeds ◽  
Lqr Controller ◽  
Optimal Linear

A key source of safety and infrastructure issues for operations of longer combination vehicles (LCVs) is off-tracking, which has been used to refer to the general phenomenon that the rear wheels of a truck do not follow the track of the front wheels and wander off the travel lane. In this paper, we examine the effectiveness of command-steering in reducing off-tracking during a 90-degree turn at low and high speeds in an articulated system with a tractor and three full trailers. In command steering, rear front axles of the trailers are steered proportionately to the articulation angle between the tractor and trailing units. We then consider several control strategies to minimize off-tracking and rearward amplification of this system. A minimum rearward amplification ratio (RWA), as a surrogate for minimum off tracking, has been used as the control criterion for medium to high speeds to arrive at an optimal Linear Quadratic Regulator (LQR) controller. As for low speeds, the maximum radial offset between the tractor and trailer 3 is minimized in the design of the controller. Robustness of the optimal controller with respect to tyre-parameter perturbations is then examined. Based on the simulation results, we find that, active command steering is very effective in reducing off tracking at low- as well as high-speed 90-degree turns. To achieve acceptable levels of RWA and off tracking, at least two of the three trailers must be actively command-steered. Among the three two-trailer-steering possibilities, actively steering trailers 1 and 2 is most cost-effective and results in the lowest RWA for medium- to high- speeds (at which RWA is important), and off-tracking is practically eliminated for all speed regimes considered.

Vehicle Stability Improvement by Active Front Steering Control

2007 ◽  
Author(s):  
Deling Chen ◽  
Chengliang Yin ◽  
Li Chen
Keyword(s):  
Time Estimation ◽  
Linear Quadratic Regulator ◽  
Steering System ◽  
Angle Measurement ◽  
Vehicle Stability ◽  
Steering Control ◽  
Linear Quadratic ◽  
Sideslip Angle ◽  
Feedback Parameter ◽  
Active Front Steering

This paper presents the vehicle stability improvement by active front steering (AFS) control. Firstly, a mathematical model of the steering system incorporating vehicle dynamics is analyzed based on the structure of the AFS system. Then feedback controller with linear quadratic regulator (LQR) optimization is proposed. In the controller, the assisted motor in the system is controlled by the combination of feedforward method and feedback method. And the feedback parameter is the yaw rate together with the sideslip angle. Due to the difficulties associated with the sideslip angle measurement of vehicle, a state observer is designed to provide real time estimation to meet the demands of feedback. In the last, the system is simulated in MATLAB. The results show that the vehicle handling stability is improved with the AFS control, and the effectiveness of the control system is demonstrated.

A novel adaptive-rear axles steering controller for an 8 × 8 combat vehicle

2021 ◽  
pp. 095440622110099
Author(s):  
Moataz Ahmed ◽  
Moustafa El-Gindy ◽  
Haoxiang Lang
Keyword(s):  
Sliding Mode ◽  
Linear Quadratic Regulator ◽  
Rough Terrain ◽  
Lateral Stability ◽  
Linear Quadratic ◽  
Simulation Based ◽  
Combat Vehicle ◽  
Lqr Controller ◽  
Stability Enhancement ◽  
Gain Scheduled

Multi-axle vehicles are widely used in several applications such as transportation, industrial, and military field, because of its higher reliability in comparison with conventional two axles vehicles. Despite that, there is a paucity of research studies that consider lateral stability enhancement of these vehicles, especially on rough terrain. This simulation-based research study fills this gap and introduces a new adaptive Active Rear Steering (ARS) controller that improves the lateral stability of an 8x8 combat vehicle for rough-terrain operation. The developed controller is designed utilizing the Integral Sliding Mode Control theory (ISMC) based on Gain-Scheduled Linear Quadratic Regulator (GSLQR). Besides, the GSLQR control gains are optimized by a Genetic Algorithm (GA) toolbox using a new synthesized cost function to ensure asymptotic stability. Furthermore, a new Adaptive-ISMC (AISMC) is introduced by using genetic programming to generate control equations that can replace the developed high-dimension GSLQR gains and facilitate future hardware implementation. The developed controller is evaluated by performing a series of simulation-based Double Lane Change (DLC) maneuvers on several rough terrains. The evaluation is conducted for both high friction and slippery surfaces at high and moderate speed, consequently. The results show high fidelity and robustness of the developed controller in comparison with a previously designed optimal LQR controller.

scholarly journals Design of an Optimal Linear Quadratic Regulator (LQR) Controller for the Ball-On-Sphere System

2020 ◽  
Vol 10 (3) ◽  
pp. 56-70
Author(s):  
Mohammed Usman ◽  
◽  
U. Hussein Suleiman ◽  
Muhammad Usman ◽  
Thomas Sadiq ◽  
...  
Keyword(s):  
Linear Quadratic Regulator ◽  
Linear Quadratic ◽  
Lqr Controller ◽  
Optimal Linear

Robust stabilization control of a spatial inverted pendulum using integral sliding mode controller

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Ishan Chawla ◽  
Vikram Chopra ◽  
Ashish Singla
Keyword(s):  
Inverted Pendulum ◽  
Sliding Mode ◽  
Robust Stabilization ◽  
Linear Quadratic Regulator ◽  
Humanoid Robots ◽  
Sliding Mode Controller ◽  
Linear Quadratic ◽  
Integral Sliding Mode ◽  
Wide Range ◽  
Lqr Controller

AbstractFrom the last few decades, inverted pendulums have become a benchmark problem in dynamics and control theory. Due to their inherit nature of nonlinearity, instability and underactuation, these are widely used to verify and implement emerging control techniques. Moreover, the dynamics of inverted pendulum systems resemble many real-world systems such as segways, humanoid robots etc. In the literature, a wide range of controllers had been tested on this problem, out of which, the most robust being the sliding mode controller while the most optimal being the linear quadratic regulator (LQR) controller. The former has a problem of non-robust reachability phase while the later lacks the property of robustness. To address these issues in both the controllers, this paper presents the novel implementation of integral sliding mode controller (ISMC) for stabilization of a spatial inverted pendulum (SIP), also known as an x-y-z inverted pendulum. The structure has three control inputs and five controlled outputs. Mathematical modeling of the system is done using Euler Lagrange approach. ISMC has an advantage of eliminating non-robust reachability phase along with enhancing the robustness of the nominal controller (LQR Controller). To validate the robustness of ISMC to matched uncertainties, an input disturbance is added to the nonlinear model of the system. Simulation results on two different case studies demonstrate that the proposed controller is more robust as compared to conventional LQR controller. Furthermore, the problem of chattering in the controller is dealt by smoothening the controller inputs to the system with insignificant loss in robustness.

Modeling and Stability Enhancement of Wind Turbine using Linear Quadratic Regulator

2020 ◽  
Author(s):  
Shaharyar Yousaf ◽  
Neelam Mughees ◽  
Abdullah Mughees ◽  
Ali Abbas ◽  
Syed Zulqadar Hassan ◽  
...  
Keyword(s):  
Wind Turbine ◽  
Linear Quadratic Regulator ◽  
Linear Quadratic ◽  
Stability Enhancement
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