Feedback Linearization and Extended State Observer-Based Control for Rotor-AMBs System With Mismatched Uncertainties

Liu, Chao; Liu, Gang; Fang, Jiancheng

doi:10.1109/tie.2016.2612622

Cited by 69 publications

(41 citation statements)

References 38 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Several examples of those applications are the following: [38] where the authors use feedback linearization with linear-quadratic regulator to control Stewart robot; [22,24] where feedback linearization in combination with sliding mode control is used to control induction motor drives; or [34] where, for spring loaded inverted pendulum as a model for legged locomotion, the authors use partial feedback linearization. Additionally, feedback linearization is applied also when the problem of uncertainties occurs, as in [43] where the authors consider control of nonlinear hydraulic generator with external disturbances and system uncertainty; in [25] where feedback linearization and extended state observer based control is proposed that deals with uncertainties of rotor-active magnetic bearings system; or in [46] where a neural network-based supple-mentary control system for a nonlinear plant is build on the basis of feedback linearization. The feedback linearization method is also still developed, as in [23], where the authors propose the variant of the method for systems with time varying delays.…”

Section: Introductionmentioning

confidence: 99%

Introduction of Feedback Linearization to Robust LQR and LQI Control – Analysis of Results from an Unmanned Bicycle Robot with Reaction Wheel

Owczarkowski¹,

Horla

Ziętkiewicz

2018

Asian Journal of Control

View full text Add to dashboard Cite

In this paper, the Jacobian-linearization-and feedback-linearization-based techniques of obtaining linearized model approaches are combined with a family of robust LQR control laws to identify the pairing which results in superior control performance of the bicycle robot, despite uncertainty and constraints, what is the main contribution of the paper. The control performance is analyzed using various indices, related, e.g. to energy consumption of the considered laws, with the experiments conducted on a real bicycle robot. As a result, the easily-implementable controller is obtained, which requires only to perform a set of off-line computations with a single additional parameter in comparison with a standard linear-quadratic controller, to obtain a state-feedback vector, which, when implemented to the control system, ensures proper regulation of the output signal of the plant, despite uncertainty or possible actuator failures, obtaining energy-efficient control law.

show abstract

Section: Introductionmentioning

confidence: 99%

Introduction of Feedback Linearization to Robust LQR and LQI Control – Analysis of Results from an Unmanned Bicycle Robot with Reaction Wheel

Owczarkowski¹,

Horla

Ziętkiewicz

2018

Asian Journal of Control

View full text Add to dashboard Cite

show abstract

“…Finally, the simulation results show the effectiveness, robustness, and good adaptability of the designed controller. The proposed design idea of reducing the tracking error can be extended to the tracking control of other types of systems [26][27][28][29][30][31][32][33][34][35][36][37][38][39][40] to improve the tracking accuracy and disturbance rejection performance of the controller.…”

Section: A Novel Robust Tracking Control Approach Based Onmentioning

confidence: 99%

“…Similar to the gain settings of the LESO in many other types of control systems, [29][30][31][32][33][34][35][36][37][38][39][40] the LESO with fixed preset observation gains is used in the tracking control of the antagonistic VSA based on ENTS. 40 However, the LESO with fixed preset observation gains always has estimation errors, especially when the reference trajectories change abruptly (i.e.…”

Section: Introductionmentioning

confidence: 99%

Robust tracking control for two classes of variable stiffness actuators based on linear extended state observer with estimation error compensation

Guo

Xiao

2020

International Journal of Advanced Robotic Systems

View full text Add to dashboard Cite

In this article, a novel robust tracking control scheme based on linear extended state observer with estimation error compensation is proposed for the tracking control of the antagonistic variable stiffness actuator based on equivalent nonlinear torsion spring and the serial variable stiffness actuator based on lever mechanism. For the dynamic models of these two classes of variable stiffness actuators, considering the parametric uncertainties, the unknown friction torques acting on the driving units, the unknown external disturbances acting on the output links and the input saturation constraints, an integral chain pseudo-linear system with input saturation constraints and matched lumped disturbances is established by coordinate transformation. Subsequently, the matched lumped disturbances in the pseudo-linear system are extended to the new system states, and we obtain an extended integral chain pseudo-linear system. Then, we design the linear extended state observer to estimate the unknown states of the extended pseudo-linear system. Considering the input saturation constraints in the extended pseudo-linear system and the estimation errors of the linear extended state observer with fixed preset observation gains, the adaptive input saturation compensation laws and the novel estimation error compensators are designed. Finally, a robust tracking controller based on linear extended state observer, sliding mode control, adaptive input saturation compensation laws, and estimating error compensators is designed to achieve simultaneous position and stiffness tracking control of these two classes of variable stiffness actuators. Under the action of the designed controller, the semi-global uniformly ultimately bounded stability of the closed-loop system is proved by the stability analysis of the candidate Lyapunov function. The simulation results show the effectiveness, robustness, and adaptability of the designed controller in the tracking control of these two classes of variable stiffness actuators. Furthermore, the simulation comparisons show the effectiveness of the proposed estimation error compensation measures in reducing the tracking errors and improving the disturbance rejection performance of the controller.

show abstract

“…In order to obtain a good dynamic process and noise suppression capability, the characteristic equation is set as shown in the following equation, where λ q and λ k are both negative values. Their values can be selected using the bandwidth concept [38].…”

Section: The Linear Extended State Observer Designmentioning

confidence: 99%

Research on Angle and Stiffness Cooperative Tracking Control of VSJ of Space Manipulator Based on LESO and NSFAR Control

Hong

Dong

2019

Electronics

View full text Add to dashboard Cite

With the increase in on-orbit maintenance and support requirements, the application of space manipulator is becoming more promising. However, how to control the vibration generated by the space manipulator has been a difficult problem to be solved. The advent of variable stiffness joint (VSJ) has brought about a dawn in solving this problem. But how to achieve coordinated control of joint angle and stiffness is still a problem to be solved, especially when considering system model parameter uncertainty, unknown disturbance and control input saturation. In order to realize the controllable attenuation of the vibration of the space flexible manipulator based on the variable stiffness joint, the dynamic model of the variable stiffness joint was constructed. Then the linear transformation and feedback linearization method are used to transform its complex nonlinear dynamic model system into a pseudo-linear system containing aggregate disturbance and input saturation constraints. This paper constructs a linear extended state observer (LESO) for estimating the state of unknown systems in pseudo-linear systems. Based on the idea of state feedback control, a Neural State Feedback Adaptive Robust (NSFAR) control is constructed by using Radial Basis Function Neural Network. The adaptive input saturation compensation control law is also designed by using Radial Basis Function Neural Network to deal with the input saturation compensation problem. The ultimate uniform bounded stability of the constructed system is proved by the stability analysis based on Lyapunov function. Finally, the effectiveness and superiority of the constructed tracking algorithm are verified by compared simulation and semi-physical experiment.

show abstract

Feedback Linearization and Extended State Observer-Based Control for Rotor-AMBs System With Mismatched Uncertainties

Cited by 69 publications

References 38 publications

Introduction of Feedback Linearization to Robust LQR and LQI Control – Analysis of Results from an Unmanned Bicycle Robot with Reaction Wheel

Introduction of Feedback Linearization to Robust LQR and LQI Control – Analysis of Results from an Unmanned Bicycle Robot with Reaction Wheel

Robust tracking control for two classes of variable stiffness actuators based on linear extended state observer with estimation error compensation

Research on Angle and Stiffness Cooperative Tracking Control of VSJ of Space Manipulator Based on LESO and NSFAR Control

Contact Info

Product

Resources

About