A local stabilizing control scheme using an approximate feedback linearization

1994 ◽  
Vol 39 (11) ◽  
pp. 2311-2314 ◽  
Author(s):  
Kwanghee Nam ◽  
Seongno Lee ◽  
Sangchul Won
Keyword(s):  
Feedback Linearization ◽  
Stabilizing Control ◽  
Control Scheme

scholarly journals A Novel Modified Super-Twisting Control Augmented Feedback Linearization for Wearable Robotic Systems Using Time Delay Estimation

Micromachines ◽  
2021 ◽  
Vol 12 (6) ◽  
pp. 597
Author(s):  
Brahim Brahmi ◽  
Ibrahim El Bojairami ◽  
Tanvir Ahmed ◽  
Asif Al Zubayer Swapnil ◽  
Mohammad AssadUzZaman ◽  
...  
Keyword(s):  
Time Delay ◽  
Feedback Linearization ◽  
High Performance ◽  
Time Delay Estimation ◽  
Robotic Systems ◽  
External Disturbances ◽  
Uncertain Dynamics ◽  
Control Scheme ◽  
Twisting Control ◽  
Dynamics Stability

The research presents a novel controller designed for robotic systems subject to nonlinear uncertain dynamics and external disturbances. The control scheme is based on the modified super-twisting method, input/output feedback linearization, and time delay approach. In addition, to minimize the chattering phenomenon and ensure fast convergence to the selected sliding surface, a new reaching law has been integrated with the control law. The control scheme aims to provide high performance and enhanced accuracy via limiting the effects brought by the presence of uncertain dynamics. Stability analysis of the closed-loop system was conducted using a powerful Lyapunov function, showing finite time convergence of the system’s errors. Lastly, experiments shaping rehabilitation tasks, as performed by healthy subjects, demonstrated the controller’s efficiency given its uncertain nonlinear dynamics and the external disturbances involved.

Frequency-stabilizing control scheme for islanded microgrids

2015 ◽  
Author(s):  
Fahimeh Kazempour ◽  
Eman Hammad ◽  
Abdallah Farraj ◽  
Deepa Kundur
Keyword(s):  
Stabilizing Control ◽  
Control Scheme

Application of Feedback Linearization to the Controller of CSTR

2014 ◽  
Vol 1049-1050 ◽  
pp. 850-854
Author(s):  
Lan Xiang Zhu ◽  
Zhen Wang ◽  
Ding Li Yu ◽  
Wei Wei Yang ◽  
Lei Gu ◽  
...  
Keyword(s):  
Feedback Linearization ◽  
Dynamic Performance ◽  
Linear Control ◽  
Control Input ◽  
Time Varying ◽  
Continuous Stirred Tank Reactor ◽  
Linear Control Theory ◽  
Control Scheme ◽  
Variable Substitution ◽  
Continuous Stirred Tank

Based on input-output feedback linearization scheme using the theories of differential geometry, this paper designed a controller for the continuous stirred tank reactor system which is a typical nonlinear, multi-variables, time-varying system. First, continuously different the chosen system outputs until control input appear in the expression. Then, overall linearization can be realized by input variable-substitution if some conditions are satisfied. At last, mature linear control theory is used to control the sub linear system stable. Simulation results show that the proposed control scheme is efficient and the system contains good static, dynamic performance.

Adaptive Feedback Linearization Control of SISO Nonlinear Processes Using a Self-Generating Neural Network-Based Approach

2011 ◽  
Vol 6 (1) ◽  
Author(s):  
Karim Salahshoor ◽  
Amin Sabet Kamalabady
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Adaptive Control ◽  
Feedback Linearization ◽  
Learning Algorithm ◽  
Rbf Neural Networks ◽  
Adaptive Feedback ◽  
Control Scheme ◽  
Feedback Linearization Control ◽  
Adaptive Control Scheme

This paper presents a new adaptive control scheme based on feedback linearization technique for single-input, single-output (SISO) processes with nonlinear time-varying dynamic characteristics. The proposed scheme utilizes a modified growing and pruning radial basis function (MGAP-RBF) neural network (NN) to adaptively identify two self-generating RBF neural networks for online realization of a well-known affine model structure. An extended Kalman filter (EKF) learning algorithm is developed for parameter adaptation of the MGAP-RBF neural networks. The MGAP-RBF growing and pruning criteria have been endeavored to enhance its performance for online dynamic model identification purposes. A stability analysis has been provided to ensure the asymptotic convergence of the proposed adaptive control scheme using Lyapunov criterion. Capabilities of the adaptive feedback linearization control scheme is evaluated on two nonlinear CSTR benchmark processes, demonstrating good performances for both set-point tracking and disturbance rejection objectives.

Feedforward and Feedback Optimal Control of Autonomous Profiling Monitoring Underwater Vehicle with Disturbance

2014 ◽  
Vol 602-605 ◽  
pp. 970-973 ◽  
Author(s):  
Hua Mu ◽  
Jian Yuan
Keyword(s):  
Optimal Control ◽  
Linear System ◽  
Feedback Linearization ◽  
Vertical Plane ◽  
Underwater Vehicle ◽  
Linearization Method ◽  
Control Law ◽  
Control Scheme ◽  
System States ◽  
Feedback Optimal Control

The optimal control of autonomous profiling monitoring underwater vehicle (APMUV) is investigated. Firstly, dynamics equations in vertical plane with disturbances are constructed, and the equations are converted into a linear system by feedback linearization method and then feedforward and feedback optimal control (FFOC) law is designed for the linear system. To solve the unpractical problem of the control law, we construct a disturbance observer to observe the system states to make a quick convergance of the observed system states. Numerical simulations show the effectiveness of the control scheme

scholarly journals Combination of Two Nonlinear Techniques Applied to a 3-DOF Helicopter

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
P. Ahmadi ◽  
M. Golestani ◽  
S. Nasrollahi ◽  
A. R. Vali
Keyword(s):  
Convergence Rate ◽  
Feedback Linearization ◽  
Sliding Mode ◽  
Control Law ◽  
Sliding Mode Controller ◽  
Control Methods ◽  
Control Effort ◽  
Control Techniques ◽  
Control Scheme ◽  
Feedback Linearization Control

A combination of two nonlinear control techniques, fractional order sliding mode and feedback linearization control methods, is applied to 3-DOF helicopter model. Increasing of the convergence rate is obtained by using proposed controller without increasing control effort. Because the proposed control law is robust against disturbance, so we only use the upper bound information of disturbance and estimation or measurement of the disturbance is not required. The performance of the proposed control scheme is compared with integer order sliding mode controller and results are justified by the simulation.

A Cyber-Enabled Stabilizing Control Scheme for Resilient Smart Grid Systems

2016 ◽  
Vol 7 (4) ◽  
pp. 1856-1865 ◽  
Author(s):  
Abdallah Farraj ◽  
Eman Hammad ◽  
Deepa Kundur
Keyword(s):  
Smart Grid ◽  
Grid Systems ◽  
Stabilizing Control ◽  
Control Scheme

scholarly journals Robust linearization scheme by structural state feedback for a quadrotor

2021 ◽  
pp. 13-21
Author(s):  
Luis Ángel Blas-Sánchez ◽  
Margarita Galindo-Mentle ◽  
Adolfo Quiroz-Rodríguez ◽  
Marlon Licona-González
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Dynamic Model ◽  
Feedback Linearization ◽  
State Feedback ◽  
Circular Trajectory ◽  
Linearization Technique ◽  
Aerial Vehicles ◽  
State Observers ◽  
Control Scheme ◽  
Change Of Variable

In this work a feedback linearization technique is proposed, to carry it out to linearize the dynamic model of the quadrotor, a change of variable is introduced that maps the nonlinearities of the system into a nonlinear uncertainty signal contained in the domain of the action of control and is applied to the dynamic model of the quadrotor. To estimate the nonlinear uncertainty signal, the Beard-Jones filter is used, which is based on standard state observers. To verify the effectiveness of the proposed control scheme, experiments are carried out outdoors to follow a circular trajectory in the (x,y) plane. This presented control scheme is suitable for unmanned aerial vehicles where it is important to reject not only non-linearities but also to seek the simplicity and effectiveness of the control scheme for its implementation.

A Framework for Multi-Task Formation Control of Nonholonomic Robotic Systems

2008 ◽  
Author(s):  
Junjie Zhang ◽  
Jingang Yi ◽  
Suhada Jayasuriya
Keyword(s):  
Feedback Linearization ◽  
Formation Control ◽  
Null Space ◽  
Lower Layer ◽  
Hierarchical Architecture ◽  
Practical Applications ◽  
Control Scheme ◽  
Robot Systems ◽  
Asymptotic Tracking ◽  
Reference Trajectories

In practical applications, multi-robot systems may have to simultaneously deal with several tasks: collision-free maneuvers in dynamic environments; tracking certain desired trajectories; forming suitable patterns or geometrical shapes, and/or varying the pattern when necessary. The proposed formation control scheme in this paper addresses these issues. First a dynamic model for a nonholonomic robot prototype is developed. Tracking control is then realized by employing input-output feedback linearization. To achieve typical complex formation missions, a two-layer hierarchical architecture is proposed. At the upper layer, a null-space method is utilized to prioritize the tasks of the robot team and to generate reference trajectories for formation control. In the lower layer, the control scheme for each individual robot guarantees asymptotic tracking of the desired trajectories. Numerical simulations of a realistic case study illustrate the effectiveness of the proposed framework.

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