Design of Active Steering and Intelligent Braking Systems for Road Vehicle Handling Improvement: a Robust Control Approach

2006 ◽  
Author(s):  
S. Caglar Baslamish ◽  
I. Emre Kose ◽  
Gunay Anlas
Keyword(s):  
Robust Control ◽  
Road Vehicle ◽  
Vehicle Handling ◽  
Control Approach ◽  
Active Steering

Gain-scheduling robust control for a tire-blow-out road vehicle

2018 ◽  
Vol 233 (2) ◽  
pp. 344-362 ◽  
Author(s):  
Houhua Jing ◽  
Zhiyuan Liu
Keyword(s):  
Robust Control ◽  
Gain Scheduling ◽  
Front Wheel ◽  
Testing System ◽  
Road Vehicle ◽  
Control Approach ◽  
Yaw Control ◽  
Control Moment ◽  
Vehicle Velocity ◽  
Driving Stability

This paper presents a robust control approach to keeping directional and driving stability for a road vehicle after a tire blow-out. Considering the time-varying vehicle velocity as well as the uncertain tire characteristics, a linear parameter varying vehicle model is built. With front wheel steering angle and yaw control moment as control inputs, a gain-scheduling H∞ controller is developed to attenuate the effects of a flat tire. An optimal control allocation law is presented to perform the yaw control moment by differential braking on the other three tires. Finally, a hardware-in-the-loop testing system, composed of the veDYNA high-fidelity software program and an actual automotive hydraulic braking system, is utilized for controller validation. The results clearly demonstrate the effectiveness of the proposed coordinated controller in improving vehicle directional stability and robustness against the disturbances caused by a tire blow-out.

A Robust Control Approach for Primary Frequency Regulation through Variable Speed Wind Turbines

2010 ◽  
Vol 130 (11) ◽  
pp. 1002-1009 ◽  
Author(s):  
Jorge Morel ◽  
Hassan Bevrani ◽  
Teruhiko Ishii ◽  
Takashi Hiyama
Keyword(s):  
Robust Control ◽  
Wind Turbines ◽  
Frequency Regulation ◽  
Variable Speed ◽  
Control Approach ◽  
Primary Frequency

scholarly journals Adaptive Optimal Robust Control for Uncertain Nonlinear Systems Using Neural Network Approximation in Policy Iteration

2021 ◽  
Vol 11 (5) ◽  
pp. 2312
Author(s):  
Dengguo Xu ◽  
Qinglin Wang ◽  
Yuan Li
Keyword(s):  
Neural Network ◽  
Optimal Control ◽  
Robust Control ◽  
Nonlinear Systems ◽  
Policy Iteration ◽  
Control Law ◽  
Globally Asymptotically Stable ◽  
Control Approach ◽  
Input Uncertainties ◽  
Theoretical Results

In this study, based on the policy iteration (PI) in reinforcement learning (RL), an optimal adaptive control approach is established to solve robust control problems of nonlinear systems with internal and input uncertainties. First, the robust control is converted into solving an optimal control containing a nominal or auxiliary system with a predefined performance index. It is demonstrated that the optimal control law enables the considered system globally asymptotically stable for all admissible uncertainties. Second, based on the Bellman optimality principle, the online PI algorithms are proposed to calculate robust controllers for the matched and the mismatched uncertain systems. The approximate structure of the robust control law is obtained by approximating the optimal cost function with neural network in PI algorithms. Finally, in order to illustrate the availability of the proposed algorithm and theoretical results, some numerical examples are provided.

Wavelet Neural Network Based Adaptive Robust Control for a Class of MIMO Nonlinear Systems

2011 ◽  
Vol 383-390 ◽  
pp. 290-296
Author(s):  
Yong Hong Zhu ◽  
Wen Zhong Gao
Keyword(s):  
Neural Network ◽  
Robust Control ◽  
Nonlinear Systems ◽  
Wavelet Neural Network ◽  
Adaptive Robust Control ◽  
Loop Control ◽  
Control Approach ◽  
Mimo Nonlinear Systems ◽  
Output Tracking Control ◽  
Dynamic Inverse

Wavelet neural network based adaptive robust output tracking control approach is proposed for a class of MIMO nonlinear systems with unknown nonlinearities in this paper. A wavelet network is constructed as an alternative to a neural network to approximate unknown nonlinearities of the classes of systems. The proposed WNN adaptive law is used to compensate the dynamic inverse errors of the classes of systems. The robust control law is designed to attenuate the effects of approximate errors and external disturbances. It is proved that the controller proposed can guarantee that all the signals in the closed-loop control system are uniformly ultimately bounded (UUB) in the sense of Lyapunov. In the end, a simulation example is presented to illustrate the effectiveness and the applicability of the suggested method.

Performance improvement of direct torque control for induction motor drive via fuzzy logic-feedback linearization

2019 ◽  
Vol 38 (2) ◽  
pp. 672-692 ◽  
Author(s):  
Abdelkarim Ammar
Keyword(s):  
Fuzzy Logic ◽  
Robust Control ◽  
Feedback Linearization ◽  
Control Algorithm ◽  
Direct Torque Control ◽  
Torque Control ◽  
Motor Drive ◽  
Induction Motor Drive ◽  
Content Type ◽  
Control Approach

Purpose This paper aims to propose an improved direct torque control (DTC) for the induction motor’s performance enhancement using dual nonlinear techniques. The exact feedback linearization is implemented to create a linear decoupled control. Besides, the fuzzy logic control approach has been inserted to generate the auxiliary control input for the feedback linearization controller. Design/methodology/approach To improve the DTC for induction motor drive, this work suggests the incorporation of two nonlinear approaches. As the classical feedback linearization suffers while the presence of uncertainties and modeling inaccuracy, it is recommended to be associated to another robust control approach to compensate the uncertainties of the model and make a robust control versus the variations of the machine parameters. Therefore, fuzzy logic controllers will be integrated as auxiliary inputs to the feedback linearization control law. Findings The simulation and the experimental validation of the proposed control algorithm show that the association of dual techniques can effectively achieve high dynamic behavior and improve the robustness against parameters variation and external disturbances. Moreover, the space vector modulation is used to preserve a fixed switching frequency, reduce ripples and low switching losses. Practical implications The theoretical, simulation and experimental studies prove that the proposed control algorithm can be used on different AC machines for variable speed drive applications such as oil drilling, traction systems and wind energy conversion systems. Originality/value The proposed DTC strategy has been developed theoretically and realized through simulation and experimental implementation. Different operation conditions have been conducted to check the ability and robustness of the control strategy, such as steady state, speed reversal maneuver, low-speed operation and parameters variation test with load application.

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