scholarly journals Adaptive Observer-Based Output Feedback Control for Two-Wheeled Self-Balancing Robot

2020 ◽  
Vol 2020 ◽  
pp. 1-16
Author(s):  
Ines Jmel ◽  
Habib Dimassi ◽  
Salim Hadj Said ◽  
Faouzi M’Sahli
Keyword(s):  
Feedback Control ◽  
Output Feedback ◽  
Control Method ◽  
Tracking Error ◽  
Output Feedback Control ◽  
High Gain ◽  
Adaptive Observer ◽  
Unknown Parameters ◽  
Control Approach ◽  
Balancing Robot

In this paper, an output feedback control approach based on an adaptive observer is developed for the two-wheeled self-balancing robot subject to unknown parameters (with nonlinear parameterization). Firstly, a high gain control method with state feedback is proposed. Then, an adaptive observer is designed to estimate the unknown state and the unknown body mass of the robot which influences the height of the center of mass. Next, the adaptive observer is combined with the designed high gain controller: a Lyapunov-based stability analysis of the closed loop system is developed to establish the convergence of the tracking error as well as estimation and adaptation errors. Simulation results assert the performance of the developed tracking control scheme for the two-wheeled self-balancing robot subject to mass variation.

scholarly journals Adaptive Fuzzy Fault-Tolerant Output Feedback Tracking Control of Uncertain Stochastic Nonlinear Systems with Unknown Time-Delay and Tracking Error Constrained

2014 ◽  
Vol 2014 ◽  
pp. 1-11
Author(s):  
Shuai Sui ◽  
Shaocheng Tong ◽  
Yongming Li
Keyword(s):  
Time Delay ◽  
Feedback Control ◽  
Nonlinear Systems ◽  
Output Feedback ◽  
Tracking Error ◽  
Output Feedback Control ◽  
Adaptive Observer ◽  
Stochastic Nonlinear Systems ◽  
Adaptive Fuzzy ◽  
Fuzzy Adaptive

The problem of tracking error constrained adaptive fuzzy output feedback control is investigated for a class of single-input and single-output (SISO) stochastic nonlinear systems with actuator faults, unknown time-delay, and unmeasured states. The considered faults are modeled as both loss of effectiveness and lock-in-place. The fuzzy logic systems are used to approximate the unknown nonlinear functions, and a fuzzy adaptive observer is designed for estimating the unmeasured states. By transforming the tracking errors into new virtual error variables and based on backstepping recursive design technique, a new fuzzy adaptive output feedback control method is developed. It is shown that all the signals of the resulting closed-loop system are bounded in probability and the tracking error remains an adjustable neighborhood of the origin within the prescribed bounds. The simulation results are provided to show the effectiveness of the proposed approach.

scholarly journals Adaptive output feedback control for a class of uncertain non-strict feedback systems with asymmetric time-varying output constraints

2020 ◽  
Vol 12 (9) ◽  
pp. 168781402095882
Author(s):  
Min Wan ◽  
Shanshan Huang
Keyword(s):  
Feedback Control ◽  
Output Feedback ◽  
Tracking Error ◽  
Output Feedback Control ◽  
Time Varying ◽  
Dynamic Surface ◽  
Adaptive Output Feedback Control ◽  
Output Constraints ◽  
Fuzzy State ◽  
Strict Feedback

This study investigated a novel adaptive output feedback control scheme for non-strict feedback nonlinear systems with uncertainties, disturbances, and asymmetric time-varying output constraints. Because that the states of the system are unmeasurable, we used an adaptive fuzzy state observer to obtain the estimated values of the states. To make the output and tracking error satisfy their asymmetric time-varying constraints, an asymmetric time-varying barrier Lyapunov function was adopted. To overcome the “explosion of complexity” problem, we also adopted the dynamic surface control technology. The stability of the closed-loop system was proved by the Lyapunov method, and we give two simulation examples to show the effectiveness of the proposed control method.

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