Experimental Joint Control Studies With a Flexible Two-Link System

2001 ◽  
Author(s):  
Wenwei Xu ◽  
Xiaoping Zhang ◽  
Satish S. Nair
Keyword(s):  
Adaptive Control ◽  
Control Strategy ◽  
Joint Angle ◽  
Control Design ◽  
Learning Control ◽  
Continuous Functions ◽  
Joint Control ◽  
System Uncertainties ◽  
Bounded Continuous Functions ◽  
Gaussian Network

Abstract This paper investigates experimentally an adaptive control design for a flexible two-link system considering joint angle control in the presence of system uncertainties. The system uncertainties are treated as unknown bounded continuous functions of the states and a Gaussian network is used to map the uncertainties. Experiment results show the effectiveness of the proposed learning control strategy.

Towards a new design with generic modeling and adaptive control of a transformable quadrotor

2021 ◽  
pp. 1-31
Author(s):  
S.H. Derrouaoui ◽  
Y. Bouzid ◽  
M. Guiatni
Keyword(s):  
Adaptive Control ◽  
Control Strategy ◽  
Experimental Tests ◽  
Generic Model ◽  
System Control ◽  
System A ◽  
Viable Solution ◽  
Generic Modeling ◽  
Adaptive Control Strategy ◽  
The Stability

Abstract Recently, transformable Unmanned Aerial Vehicles (UAVs) have become a subject of great interest in the field of flying systems, due to their maneuverability, agility and morphological capacities. They can be used for specific missions and in more congested spaces. Moreover, this novel class of UAVs is considered as a viable solution for providing flying robots with specific and versatile functionalities. In this paper, we propose (i) a new design of a transformable quadrotor with (ii) generic modeling and (iii) adaptive control strategy. The proposed UAV is able to change its flight configuration by rotating its four arms independently around a central body, thanks to its adaptive geometry. To simplify and lighten the prototype, a simple mechanism with a light mechanical structure is proposed. Since the Center of Gravity (CoG) of the UAV moves according to the desired morphology of the system, a variation of the inertia and the allocation matrix occurs instantly. These dynamics parameters play an important role in the system control and its stability, representing a key difference compared with the classic quadrotor. Thus, a new generic model is developed, taking into account all these variations together with aerodynamic effects. To validate this model and ensure the stability of the designed UAV, an adaptive backstepping control strategy based on the change in the flight configuration is applied. MATLAB simulations are provided to evaluate and illustrate the performance and efficiency of the proposed controller. Finally, some experimental tests are presented.

Linear Robust Adaptive Control Design Using a Nonlinear Approach

1996 ◽  
Vol 29 (1) ◽  
pp. 5162-5167 ◽  
Author(s):  
Youping Zhang ◽  
Petros A. Ioannou
Keyword(s):  
Adaptive Control ◽  
Control Design ◽  
Robust Adaptive Control ◽  
Nonlinear Approach ◽  
Robust Adaptive

Stability analysis of adaptive control using fuzzy adapting rate neural emulator: Experimental validation on a thermal process

2021 ◽  
pp. 095965182098818
Author(s):  
Fatma Ezzahra Rhili ◽  
Asma Atig ◽  
Ridha Ben Abdennour ◽  
Fabrice Druaux ◽  
Dimitri Lefebvre
Keyword(s):  
Adaptive Control ◽  
Control Strategy ◽  
Thermal Process ◽  
Experimental Validation ◽  
Experimental Simulation ◽  
Neural Controller ◽  
Control Scheme ◽  
Stability Method ◽  
Indirect Adaptive Control ◽  
Adaptive Control Scheme

In this study, an adaptive control based on fuzzy adapting rate for neural emulator of nonlinear systems having unknown dynamics is proposed. The indirect adaptive control scheme is composed by the neural emulator and the neural controller which are connected by an autonomous algorithm inspired from the real-time recurrent learning. In order to ensure stability and faster convergence, a neural controller adapting rate is established in the sense of the continuous Lyapunov stability method. Numerical simulations are included to illustrate the effectiveness of the proposed method. The performance of the proposed control strategy is also demonstrated through an experimental simulation.

Adaptive control strategy-based reference model for spacecraft motion trajectory

2014 ◽  
Vol 29 (5) ◽  
pp. 639-652 ◽  
Author(s):  
Zarina Samigulina ◽  
Olga Shiryayeva ◽  
Galina Samigulina ◽  
Hassen Fourati
Keyword(s):  
Adaptive Control ◽  
Control Strategy ◽  
Reference Model ◽  
Motion Trajectory ◽  
Spacecraft Motion ◽  
Adaptive Control Strategy

Application of Combined Feedforward and Feedback Controller With Shaped Input to Benchmark Problem

2010 ◽  
Vol 132 (2) ◽  
Author(s):  
Young Joo Shin ◽  
Peter H. Meckl
Keyword(s):  
Feedback Control ◽  
Control Strategy ◽  
Control Strategies ◽  
Control Design ◽  
Single Frequency ◽  
Benchmark Problems ◽  
Control Force ◽  
Benchmark Problem ◽  
Advantages And Disadvantages ◽  
Robust Control Design

Benchmark problems have been used to evaluate the performance of a variety of robust control design methodologies by many control engineers over the past 2 decades. A benchmark is a simple but meaningful problem to highlight the advantages and disadvantages of different control strategies. This paper verifies the performance of a new control strategy, which is called combined feedforward and feedback control with shaped input (CFFS), through a benchmark problem applied to a two-mass-spring system. CFFS, which consists of feedback and feedforward controllers and shaped input, can achieve high performance with a simple controller design. This control strategy has several unique characteristics. First, the shaped input is designed to extract energy from the flexible modes, which means that a simpler feedback control design based on a rigid-body model can be used. In addition, only a single frequency must be attenuated to reduce residual vibration of both masses. Second, only the dynamics between control force and the first mass need to be considered in designing both feedback and feedforward controllers. The proposed control strategy is applied to a benchmark problem and its performance is compared with that obtained using two alternative control strategies.

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