scholarly journals Model-Free Adaptive Control for Tank Truck Rollover Stabilization

2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Xian-Sheng Li ◽  
Yuan-Yuan Ren ◽  
Xue-Lian Zheng
Keyword(s):  
Adaptive Control ◽  
Stability Control ◽  
Strong Nonlinearity ◽  
Tank Truck ◽  
Controlled System ◽  
Model Free ◽  
Vehicle Loading ◽  
Control Objective ◽  
State Uncertainty ◽  
Vehicle Rollover

Influenced by lateral liquid sloshing in partially filled tanks, tank vehicles are apt to encounter with rollover accidents. Due to its strong nonlinearity and loading state uncertainty, it has great challenges in tank vehicle active control. Based on the model-free adaptive control (MFAC) theory, the roll stability control problem of tank trucks with different tank shapes and liquid fill percentages is explored. First, tank trucks equipped with cylinder or elliptical cylinder tanks are modelled, and vehicle dynamics is analyzed. This dynamic model is used to provide I/O data in the controlled system. Next, the control objective of tank vehicle rollover stabilization is analyzed and the controlled variable is selected. Subsequently, differential braking and active front steering controller are designed by MFAC algorithm. Finally, the effectiveness of the designed controllers is verified by simulation, and difference between the controllers is analyzed. The controller designed by MFAC algorithm is proven to be adaptive to vehicle loading and driving states. The controlled system has great robustness.

Model Free Adaptive Control for Thrust Cylinder of Water Well Drilling Rig

2020 ◽  
Author(s):  
Yao Wenlong ◽  
Qi Guanhua ◽  
Yang ke ◽  
Chi Ronghu ◽  
Yang Dejing
Keyword(s):  
Adaptive Control ◽  
Well Drilling ◽  
Drilling Rig ◽  
Model Free ◽  
Water Well

Anti-noise model-free adaptive control and its application in the circulating fluidized bed boiler

2020 ◽  
pp. 095965182097937
Author(s):  
Na Dong ◽  
Wenjin Lv ◽  
Shuo Zhu ◽  
Donghui Li
Keyword(s):  
Adaptive Control ◽  
Complete Convergence ◽  
Circulating Fluidized Bed ◽  
Control Method ◽  
Noise Model ◽  
Good Resistance ◽  
Industrial Systems ◽  
Noise Interference ◽  
Model Free ◽  
Tracking Differentiator

Model-free adaptive control has been developed greatly since it was proposed. Up to now, model-free adaptive control theory has become mature and tends to be an effective solution for complex unmodeled industrial systems. In practical industrial processes, most control systems are inevitably accompanied by noise that will result in indelible error and may further cause inaccurate feedback to the output. In order to solve this kind of problem with model-free technique, this article incorporates an improved tracking differentiator into model-free adaptive control. After that, the anti-noise model-free adaptive control method with complete convergence analysis is proposed. Meanwhile, numerical simulation proves that the improved control method can quickly track a given signal with good resistance to noise interference. Finally, the effectiveness and practicability of the proposed algorithm are verified by experiments through the control of drum water level of circulating fluidized.

Identification-Free Adaptive Separate Layer Water Injection Control Based on Expert Amendment

2010 ◽  
Vol 44-47 ◽  
pp. 1470-1475
Author(s):  
Feng Shan Wang ◽  
De Li Jia ◽  
Shu Jin Zhang ◽  
Chong Jiang Liu ◽  
De Kui Xu
Keyword(s):  
Adaptive Control ◽  
Control Strategy ◽  
Water Injection ◽  
Strong Nonlinearity ◽  
Separate Layer ◽  
Injection Control ◽  
System Output ◽  
Adaptive Control Strategy ◽  
Injection Effect ◽  
Injection Technology

An identification-free adaptive control strategy based on expert amendment is proposed in this paper to solve the problem that it is difficult to establish mathematical model of water injection regulating process due to large time delay, strong nonlinearity and time variation in the flow control of separate layer water injection technology. In this control strategy, according to the past and current process information of water injection, the system output and trend can be estimated based on expert rules to amend the output of the identification-free adaptive control. The simulation result shows that this control strategy has perfect control performance and strong adaptability and it provides a feasible means for improving water injection effect.

Model-Free Adaptive Control of STATCOM for SSO Mitigation in DFIG-based Wind Farm

2021 ◽  
pp. 1-1
Author(s):  
Xi Wu ◽  
Mengting Wang ◽  
Mohammad Shahidehpour ◽  
Shuang Feng ◽  
Xi Chen
Keyword(s):  
Adaptive Control ◽  
Wind Farm ◽  
Model Free

Experimental and Analytical Decentralized Adaptive Control of a 7-DOF Robot Manipulator

2020 ◽  
Author(s):  
Alexander Bertino ◽  
Peiman Naseradinmousavi ◽  
Atul Kelkar
Keyword(s):  
Adaptive Control ◽  
Control Strategy ◽  
Computational Efficiency ◽  
Tracking Control ◽  
Robot Manipulator ◽  
Problem Formulation ◽  
Experimental Results ◽  
Model Free ◽  
Trajectory Simulation ◽  
Adaptive Control Strategy

Abstract In this paper, we study the analytical and experimental control of a 7-DOF robot manipulator. A model-free decentralized adaptive control strategy is presented for the tracking control of the manipulator. The problem formulation and experimental results demonstrate the computational efficiency and simplicity of the proposed method. The results presented here are one of the first known experiments on a redundant 7-DOF robot. The efficacy of the adaptive decentralized controller is demonstrated experimentally by using the Baxter robot to track a desired trajectory. Simulation and experimental results clearly demonstrate the versatility, tracking performance, and computational efficiency of this method.

scholarly journals A Fault Tolerant Vehicle Stability Control Using Adaptive Control Allocation

2018 ◽  
Author(s):  
Ozan Temiz ◽  
Melih Cakmakci ◽  
Yildiray Yildiz
Keyword(s):  
Adaptive Control ◽  
Fault Tolerant ◽  
Stability Control ◽  
Steering Wheel ◽  
Slip Angle ◽  
Control Allocation ◽  
Control Input ◽  
Allocation Strategy ◽  
Virtual Control ◽  
Yaw Stability

This paper presents an integrated fault-tolerant adaptive control allocation strategy for four wheel frive - four wheel steering ground vehicles to increase yaw stability. Conventionally, control of brakes, motors and steering angles are handled separately. In this study, these actuators are controlled simultaneously using an adaptive control allocation strategy. The overall structure consists of two steps: At the first level, virtual control input consisting of the desired traction force, the desired moment correction and the required lateral force correction to maintain driver’s intention are calculated based on the driver’s steering and throttle input and vehicle’s side slip angle. Then, the allocation module determines the traction forces at each wheel, front steering angle correction and rear steering wheel angle, based on the virtual control input. Proposed strategy is validated using a non-linear three degree of freedom reduced two-track vehicle model and results demonstrate that the vehicle can successfully follow the reference motion while protecting yaw stability, even in the cases of device failure and changed road conditions.

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