scholarly journals Robust H∞ Control for Path Tracking of Network-Based Autonomous Vehicles

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Changfang Chen ◽  
Minglei Shu ◽  
Yinglong Wang ◽  
Ruixia Liu
Keyword(s):  
Autonomous Vehicles ◽  
Path Tracking ◽  
System Stability ◽  
Linear Matrix ◽  
Packet Dropout ◽  
Negative Effects ◽  
Parameter Uncertainties ◽  
Control Scheme ◽  
And Performance ◽  
Attention Level

This paper investigates the robust H∞ path-tracking control problem of network-based autonomous vehicles (AVs) with delay and packet dropout. Generally, both network-induced delay and packet dropout bring negative effects on the system stability and performance. A robust H∞ control scheme is proposed to realize the desired path tracking and lateral stability. The closed-loop system is asymptotically stable with the prescribed H∞ disturbance attention level if there exist some matrices satisfying certain linear matrix inequality (LMI) conditions. Furthermore, the proposed controller is robust to the parameter uncertainties and external disturbances. Simulation results are presented to verify the effectiveness of the proposed control scheme.

MAINTAINING SYNCHRONIZATION BY DECENTRALIZED FEEDBACK CONTROL IN TIME DELAY NEURAL NETWORKS WITH PARAMETER UNCERTAINTIES

2007 ◽  
Vol 17 (02) ◽  
pp. 115-122 ◽  
Author(s):  
MOU CHEN ◽  
CHANG-SHENG JIANG ◽  
QING-XIAN WU ◽  
WEN-HUA CHEN
Keyword(s):  
Neural Networks ◽  
Feedback Control ◽  
External Disturbance ◽  
Synchronization Error ◽  
Linear Matrix ◽  
Parameter Uncertainties ◽  
Time Varying Delay ◽  
Control Scheme ◽  
Error Dynamics ◽  
Varying Delay

A decentralized feedback control scheme is proposed to synchronize linearly coupled identical neural networks with time-varying delay and parameter uncertainties. Sufficient condition for synchronization is developed by carefully investigating the uncertain nonlinear synchronization error dynamics in this article. A procedure for designing a decentralized synchronization controller is proposed using linear matrix inequality (LMI) technique. The designed controller can drive the synchronization error to zero and overcome disruption caused by system uncertainty and external disturbance.

Modeling of an Inertially Stabilized Camera System Using Gimbal Platform

2016 ◽  
Author(s):  
Gary Haggart ◽  
Vidya K. Nandikolla ◽  
Ruting Jia
Keyword(s):  
Low Cost ◽  
System Stability ◽  
Motor Drive ◽  
Performance Limits ◽  
Camera System ◽  
Control Scheme ◽  
Selection For ◽  
And Performance ◽  
Stabilized Platform ◽  
Inertially Stabilized Platform

This paper develops a camera gimbal platform for stabilization and tracking purposes. The main focus of this research is analytical modeling of an inertially stabilized platform with the prediction of the angular stability. The mechanical model of the platform includes, moment of inertia, motor drive, and performance of the gyro to measure the disturbances of the platform. The gimbal/motor system is developed and simulated and feedback control scheme is designed to stabilize and maintain the line of sight (LOS) for tracking purposes. The model integrates a PI2 controller using a PID-I approach for the system stability. The effect of vibration induced disturbance in the system is investigated to simulate the realistic behavior of an inertially stabilized platform. The simulation results of the four types of commercial gyros are presented to calculate the required values for stability purposes. The results from the simulation generated the performance limits chart describing the working condition of the low cost sensors vs the high cost sensors. As the vibration level increased, the performance of the highest quality sensor greatly decreased. This verifies the value and necessity of modeling and simulating to understand the component trade studies to ensure correct sensor selection for the desired application.

Iterative Learning Control With Optimal Feedback and Feedforward Control

2010 ◽  
Author(s):  
Shuwen Yu ◽  
Masayoshi Tomizuka
Keyword(s):  
Control Strategy ◽  
Iterative Learning Control ◽  
Feedforward Control ◽  
Learning Control ◽  
Iterative Learning ◽  
System Stability ◽  
Optimal Feedback ◽  
Control Scheme ◽  
Combined Control ◽  
And Performance

Iterative learning control (ILC) is a feedforward control strategy used to improve the performance of a system that executes the same task repeatedly, but is incapable of compensating for non-repetitive disturbances. Thus a well-designed feedback controller needs to be used in combination with ILC. A robustness filter called the Q-filter is essential for the ILC system stability. The price to pay, however, is that the Q-filter makes it impossible for ILC to achieve perfect tracking of the repetitive reference or perfect cancellation of repetitive disturbances. To reduce error, it is effective to apply a pre-design feedforward control input in addition to ILC. In this paper, a simple P-type ILC is combined with an optimal feedback-feedforward control inspired by classic predictive control, so as to take advantages of each control strategy. It will be shown that the choice of the injection point of the learned ILC effort is crucial for a tradeoff between stability and performance. Therefore, the stability and performance analysis based on different injection points is studied. A systematic approach to the combined control scheme is also proposed. The combined control scheme is attractive due to its simplicity and promising performance. The effectiveness of the combined control scheme is verified by simulation results with a wafer scanner system.

scholarly journals Delay-Dependent Stability in Uncalibrated Image-Based Dynamic Visual Servoing Robotic System

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-14 ◽  
Author(s):  
Tao Li ◽  
Hui Zhao ◽  
Yu Chang
Keyword(s):  
Visual Servoing ◽  
Adaptive Controller ◽  
System Stability ◽  
Robotic Systems ◽  
Negative Effects ◽  
Control Scheme ◽  
The Stability ◽  
Delay Dependent ◽  
Delay Dependent Stability ◽  
The Relationship

This paper addresses the stability problem of uncalibrated image-based visual servoing robotic systems. Both the visual feedback delay and the uncalibrated visual parameters can be the sources of instability for visual servoing robotic systems. To eliminate the negative effects caused by kinematic uncertainties and delays, we propose an adaptive controller including the delay-affected Jacobian matrix and design an adaptive law accordingly. Besides, the delay-dependent stability conditions are provided to show the relationship between the system stability and the delayed time in order to obtain less conservative results. A Lyapunov-Krasovskii functional is constructed, and a rigorously mathematic proof is given. Finally, the simulation results are presented to show the effectiveness of the proposed control scheme.

scholarly journals Review and performance evaluation of path tracking controllers of autonomous vehicles

2021 ◽  
Vol 15 (5) ◽  
pp. 646-670
Author(s):  
Mohammad Rokonuzzaman ◽  
Navid Mohajer ◽  
Saeid Nahavandi ◽  
Shady Mohamed
Keyword(s):  
Performance Evaluation ◽  
Autonomous Vehicles ◽  
Path Tracking ◽  
Tracking Controllers ◽  
And Performance

Undesirable Effects of Goal Setting on Perceived Fairness, Commitment, and Unethical Behavior

2018 ◽  
Vol 62 (2) ◽  
pp. 97-107 ◽  
Author(s):  
Nina Keith
Keyword(s):  
Goal Setting ◽  
Unethical Behavior ◽  
The United States ◽  
Goal Commitment ◽  
Management Technique ◽  
Long Term Effects ◽  
Perceived Fairness ◽  
Negative Effects ◽  
Positive Effects ◽  
And Performance

Abstract. The positive effects of goal setting on motivation and performance are among the most established findings of industrial–organizational psychology. Accordingly, goal setting is a common management technique. Lately, however, potential negative effects of goal-setting, for example, on unethical behavior, are increasingly being discussed. This research replicates and extends a laboratory experiment conducted in the United States. In one of three goal conditions (do-your-best goals, consistently high goals, increasingly high goals), 101 participants worked on a search task in five rounds. Half of them (transparency yes/no) were informed at the outset about goal development. We did not find the expected effects on unethical behavior but medium-to-large effects on subjective variables: Perceived fairness of goals and goal commitment were least favorable in the increasing-goal condition, particularly in later goal rounds. Results indicate that when designing goal-setting interventions, organizations may consider potential undesirable long-term effects.

Robust H2 Output Feedback Controller Design for Damping Power System Oscillations

2017 ◽  
Vol 6 (10) ◽  
pp. 8
Author(s):  
Kho Hie Kwee ◽  
Hardiansyah .
Keyword(s):  
Power System ◽  
Output Feedback ◽  
Controller Design ◽  
Sufficient Conditions ◽  
Feedback Controller ◽  
Linear Matrix ◽  
Parameter Uncertainties ◽  
Worst Case ◽  
Output Feedback Controller ◽  
Power System Oscillations

This paper addresses the design problem of robust H2 output feedback controller design for damping power system oscillations. Sufficient conditions for the existence of output feedback controllers with norm-bounded parameter uncertainties are given in terms of linear matrix inequalities (LMIs). Furthermore, a convex optimization problem with LMI constraints is formulated to design the output feedback controller which minimizes an upper bound on the worst-case H2 norm for a range of admissible plant perturbations. The technique is illustrated with applications to the design of stabilizer for a single-machine infinite-bus (SMIB) power system. The LMI based control ensures adequate damping for widely varying system operating.

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