Feedback Game-Based Shared Control Scheme Design for Emergency Collision Avoidance: A Fuzzy-Linear Quadratic Regulator Approach

2019 ◽  
Vol 141 (8) ◽  
Author(s):  
Xuewu Ji ◽  
Kaiming Yang ◽  
Xiaoxiang Na ◽  
Chen Lv ◽  
Yulong Liu ◽  
...  
Keyword(s):  
Collision Avoidance ◽  
Piecewise Linear ◽  
Linear Quadratic Regulator ◽  
Stackelberg Equilibrium ◽  
Shared Control ◽  
Equilibrium Solutions ◽  
Linear Quadratic ◽  
Scheme Design ◽  
Control Scheme ◽  
Lq Problem

Driver-machine shared control scheme opens up a new frontier for the design of driver assistance system, especially for improving active safety in emergency scenario. However, the driver's stress response to steering assistance and strong tire nonlinearity are main challenges suffered by controller designing for collision avoidance. These unfavorable factors are particularly pronounced during emergency steering maneuvers and sharply degrade shared control performance. This paper proposes a fuzzy-linear quadratic regulator (LQR) game-based control scheme to simultaneously enhance vehicle stability while compensating driver's inappropriate steering reaction in emergency avoidance. A piecewise linear-based Takagi–Sugeno (T–S) fuzzy structure is presented to mimic driver's knowledge about vehicle lateral nonlinearity, and the control authority is shared between driver and emergency steering assistance (ESA) system through steer-by-wire (SBW) assembly. An identical piecewise internal model is chosen for ESA and the shared lane-keeping problem is modeled as a fuzzy linear quadratic (LQ) problem, where the symmetrical fuzzy structure further enhances vehicle's ability to handle extreme driving conditions. In particular, the feedback Stackelberg equilibrium solutions of the fuzzy-LQ problem are derived to describe the interactive steering behavior of both agents, which enables the ESA to compensate driver's irrational steering reaction. Hardware-in-the-loop (HIL) experiment demonstrates the ESA's capability in compensating driver's aggressive steering behavior, as well as the copiloting system's excellent tracking and stabilizing performance in emergency collision avoidance.

FULL-AND REDUCED- ORDER COMPENSATOR FOR INNOSAT ATTITUDE CONTROL

2015 ◽  
Vol 76 (12) ◽  
Author(s):  
Fadzilah Hashim ◽  
Mohd Yusoff Mashor ◽  
Siti Maryam Sharun
Keyword(s):  
State Space ◽  
Attitude Control ◽  
Space Form ◽  
Transfer Functions ◽  
Linear Quadratic Regulator ◽  
Linear Quadratic ◽  
Reduced Order ◽  
Lqr Control ◽  
Best Value ◽  
Control Scheme

This paper presents a study on the estimator based on Linear Quadratic Regulator (LQR) control scheme for Innovative Satellite (InnoSAT). By using LQR control scheme, the controller and the estimator has been derived for state space form in all three axes to stabilize the system’s performance. This study starts by converting the transfer functions of attitude control into state space form.  Then, the step continues by finding the best value of weighting matrices of LQR in order to obtain the best value of controller gain, K. After that, the best value of L is obtained for the estimator gain. The value of K and L is combined in forming full order compensator and in the same time the reduced order compensator is also formed. Lastly, the performance of full order compensator is compared to reduced order compensator. From the simulation, results indicate that both types of estimators have presented good stability and tracking performance. However, reduced order estimator has simpler equation and faster convergence to zero than the full order estimator. This property is very important in developing a satellite attitude control for real-time implementation.

Backstepping Controller Design for a 5 DOF Spherical Inverted Pendulum

2019 ◽  
Vol 41 ◽  
pp. 37-50 ◽  
Author(s):  
Soukaina Krafes ◽  
Zakaria Chalh ◽  
Abdelmjid Saka
Keyword(s):  
Degrees Of Freedom ◽  
Inverted Pendulum ◽  
Controller Design ◽  
Linear Quadratic Regulator ◽  
Performance Comparison ◽  
Virtual Reality Environment ◽  
Linear Quadratic ◽  
Control Scheme ◽  
Linearized System ◽  
Backstepping Controller

This paper presents a Backstepping controller for five degrees of freedom Spherical Inverted Pendulum. Since the system is nonlinear, unstable, underactuated and MIMO and has a nonsquare form, the classic control design cannot be applied to control it. In order to remedy this problem, we propose in this paper a new method based on hierarchical steps of the Backstepping controller taking into a count the nonlinearities that cannot be neglected. Furthermore, a Linear Quadratic Regulator controller and LQR + PID based on the linearized system model are also designed for performance comparison. Finally, a simulation study is carried out to prove the effectiveness of proposed control scheme and is validated using the virtual reality environment that proves the performance of the Backstepping controller over the linear ones where it brings the pendulum from any initial condition in the upper hemisphere while the base is brought to the origin of the coordinates.

Delayed Reference Control of a Two-Mass Elastic System

2004 ◽  
Vol 10 (1) ◽  
pp. 135-159 ◽  
Author(s):  
P Gallina ◽  
Alberto Trevisani
Keyword(s):  
Elastic System ◽  
Linear Quadratic Regulator ◽  
Primary Concern ◽  
Linear Quadratic ◽  
Mass System ◽  
Control Scheme ◽  
Optimal Linear ◽  
Reference Parameter ◽  
The Stability

An innovative non-time-based control scheme for path tracking and vibration control of a two-mass system is introduced in this paper. The basic idea of the scheme, called delayed reference control (DRC), is to make the path reference of the system be a function of an action reference parameter which depends both on time and a variable which plays the role of a time delay. By suitably computing the value of the delay on the basis of the vibration measured, such vibration can be actively suppressed while an independent position regulator ensures an accurate tracking of the desired path. The DRC scheme is therefore suitable for those applications, in particular in the robotic field, where a pre-defined path through space must be followed precisely while the time taken to carry out the task is not a primary concern. In this paper the stability of the system is investigated, and numerical results are provided to assess the performance of the proposed method, compared to that of an optimal linear quadratic regulator.

CONTROL OF TWO-WHEELED INVERTED PENDULUM ROBOT USING ROBUST PI AND LQR CONTROLLERS

2020 ◽  
pp. 1-15
Author(s):  
Nguyen Hoai Nam
Keyword(s):  
Inverted Pendulum ◽  
Linear Quadratic Regulator ◽  
Pi Controller ◽  
Linear Quadratic ◽  
Control Loops ◽  
Dc Motors ◽  
Wheeled Inverted Pendulum ◽  
Control Scheme ◽  
Lqr Controller ◽  
Heading Angle

In this paper, a robust PI controller in combination with a linear quadratic regulator (LQR) is proposed to control a two-wheeled inverted pendulum robot (TWIPR) such that it is kept balanced while moving. The proposed TWIPR control system consists of two control loops. The inner loop has two PI controllers for two DC motors’ currents, which are separately designed based on a robust PI controller structure. The outer loop contains a LQR controller for the tilt angle, heading angle and position of the TWIPR. The proposed PI controller is compared to the existing method such as the magnitude optimum (MO) and genetic algorithm (GA) methods. The proposed control scheme is verified through simulations and practical tests, and it is also compared to the MO-LQR and GA-LQR strategies.

A Control Scheme for an Opposed Recumbent Tandem Human-Powered Bicycle

1996 ◽  
Vol 12 (4) ◽  
pp. 480-492
Author(s):  
Scott O. Cloyd ◽  
Mont Hubbard ◽  
LeRoy W. Alaways
Keyword(s):  
Feedback Control ◽  
Linear Quadratic Regulator ◽  
Optimal Feedback Control ◽  
State Variables ◽  
Linear Quadratic ◽  
Lateral Deviation ◽  
Control Scheme ◽  
Control Schemes ◽  
Lean Angle ◽  
Human Powered

Feedback control of a human-powered single-track bicycle is investigated through the use of a linearized dynamical model in order to develop feedback gains that can be implemented by a human pilot in an actual vehicle. The object of the control scheme is to satisfy two goals: balance and tracking. The pilot should be able not only to keep the vehicle upright but also to direct the forward motion as desired. The two control inputs, steering angle and rider lean angle, are assumed to be determined by the rider as a product of feedback gains and “measured” values of the state variables: vehicle lean, lateral deviation from the desired trajectory, and their derivatives. Feedback gains are determined through linear quadratic regulator theory. This results in two control schemes, a “full” optimal feedback control and a less complicated technique that is more likely to be usable by an inexperienced pilot. Theoretical optimally controlled trajectories are compared with experimental trajectories in a lane change maneuver.

scholarly journals Hierarchical Lateral Control Scheme for Autonomous Vehicle with Uneven Time Delays Induced by Vision Sensors

Sensors ◽  
2018 ◽  
Vol 18 (8) ◽  
pp. 2544 ◽  
Author(s):  
Qi Liu ◽  
Yahui Liu ◽  
Congzhi Liu ◽  
Baiming Chen ◽  
Wenhao Zhang ◽  
...  
Keyword(s):  
Time Delays ◽  
Low Cost ◽  
Computational Cost ◽  
Linear Quadratic Regulator ◽  
Threshold Method ◽  
Linear Quadratic ◽  
Lateral Control ◽  
Online Computation ◽  
Control Scheme ◽  
Lqr Controller

Vision-based sensors are widely used in lateral control of autonomous vehicles, but the large computational cost of the visual algorithms often induces uneven time delays. In this paper, a hierarchical vision-based lateral control scheme is proposed, where the upper controller is designed by robust H∞-based linear quadratic regulator (LQR) algorithm to compensate sensor-induced delays, and the lower controller is based on logic threshold method, in order to achieve strong convergence of the steering angle. Firstly, the vehicle lateral model is built, and the nonlinear uncertainties induced by time delays are linearized with Taylor expansion. Secondly, the state space of the system is augmented to describe such uncertainties with polytopic inclusions, which is controlled by an H∞-based LQR controller with a low cost of online computation. Then, a lower controller is designed for the control of the steering motor. According to the results of the vehicle experiment as well as the hardware-in-the-loop (HIL) experiment, the proposed control scheme shows good performance in vehicle’s lateral control task, and exhibits better robustness compared with a conventional LQR controller. The proposed control scheme provides a feasible solution for the lateral control of autonomous driving.

Optimal preview position control for shifting actuators of automated manual transmission

2018 ◽  
Vol 233 (2) ◽  
pp. 440-452
Author(s):  
Zhiqiang Chen ◽  
Bangji Zhang ◽  
Nong Zhang ◽  
Haiping Du ◽  
Guoling Kong
Keyword(s):  
Position Control ◽  
Linear Quadratic Regulator ◽  
Transformation Method ◽  
State Feedback Control ◽  
Linear Matrix ◽  
Linear Quadratic ◽  
State Transformation ◽  
Gear Shift ◽  
Shift Quality ◽  
Control Scheme

This paper is concerned with the problem of position tracking control for the motor-driven gear-shift actuating mechanism for electro-mechanical automated manual transmissions (AMT). It is well known that torque interruption is an inherent flaw of AMT. As shift duration directly affects the torque interruption interval, shift quality can be improved by minimizing the duration of the shift. To realize rapid and precise gear-shift control, an optimal discrete-time preview position control scheme is proposed. The proposed control scheme consists of state-feedback control, a discrete integrator, and preview feed-forward control. Instead of the traditional difference method, the state transformation method is utilized to construct the augmented error system such that the augmented system can be kept in a simple form. The H∞ performance index is employed to reduce the effect of the shifting load disturbance during the gear-shifting process. The controller gains are obtained by solving a linear matrix inequality (LMI). Simulation and test bench results all show that the proposed preview control algorithm has better dynamic response and adaptability under different loads compared to the optimal linear quadratic regulator (LQR) controller and the standard PID controller.

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