Trajectory tracking of under-actuated quadcopter using Lyapunov-based optimum adaptive controller

2021 ◽  
pp. 095441002110108
Author(s):  
M Navabi ◽  
Ali Davoodi ◽  
Hamidreza Mirzaei
Keyword(s):  
Trajectory Tracking ◽  
Sliding Mode ◽  
Pso Algorithm ◽  
Adaptive Controller ◽  
Closed Loop System ◽  
Parameter Uncertainties ◽  
Trajectory Tracking Control ◽  
Adaptive Sliding Mode Controller ◽  
Backstepping Controller ◽  
Flying Robot

In this article, optimum adaptive sliding mode controller (ASMC) optimized by particle swarm optimization (PSO) algorithm is designed to solve the trajectory tracking control problems of a quadcopter with model parameter uncertainties. Quadcopters have nonlinear, multi-input multi-output, coupled and under-actuated dynamics. For comparison with the designed controller, an adaptive integral backstepping controller approach is applied to compensate mass and inertia uncertainties of the flying robot. These methods guarantee stability of closed-loop system and force the states to track desired reference signals. The performance of both controllers is evaluated by numerical simulations. The obtained results demonstrate the better effectiveness of the designed PSO ASMC in stabilization of tracking particularly with parameter uncertainties.

The Leveling Position Control of a Four-Axial Active Pneumatic Isolation System Using PWM-Driving Parallel Dual-On/Off Valves

2011 ◽  
Vol 110-116 ◽  
pp. 3176-3183 ◽  
Author(s):  
Mao Hsiung Chiang ◽  
Hao Ting Lin
Keyword(s):  
Trajectory Tracking ◽  
Vibration Isolation ◽  
Position Control ◽  
Controller Design ◽  
Sliding Mode ◽  
Tracking Performance ◽  
Trajectory Tracking Control ◽  
Isolation System ◽  
Adaptive Sliding Mode Controller ◽  
Novel Concept

This study aims to develop a leveling position control of an active PWM-controlled pneumatic isolation table system. A novel concept using parallel dual-on/off valves with PWM control signals is implemented to realize active control and to improve the conventional pneumatic isolation table that supported by four pneumatic cushion isolators. In this study, the cushion isolators are not only passive vibration isolation devices, but also pneumatic actuators in active position control. Four independent closed-loop position feedback control system are designed and implemented for the four axial isolators. In this study, on/off valves are used, and PWM is realized by software. Therefore, additional hardware circuit is not required to implement PWM and not only cost down but also reach control precision of demand. In the controller design, the Fourier series-based adaptive sliding-mode controller with H∞ tracking performance is used to deal with the uncertainty and time-varying problems of pneumatic system. Finally, the experiments on the pneumatic isolation table system for synchronous position and trajectory tracking control, including no-load and loading conditions, and synchronous position control with master-slave method, are implemented in order to verify that the controller for each cushion isolator can realize good position and trajectory tracking performance.

scholarly journals Adaptive Sliding Mode Trajectory Tracking Control for WMR Considering Skidding and Slipping via Extended State Observer

Energies ◽  
2019 ◽  
Vol 12 (17) ◽  
pp. 3305 ◽  
Author(s):  
Gang Wang ◽  
Chenghui Zhou ◽  
Yu Yu ◽  
Xiaoping Liu
Keyword(s):  
Trajectory Tracking ◽  
Tracking Control ◽  
Sliding Mode ◽  
External Disturbance ◽  
State Observer ◽  
Extended State Observer ◽  
Extended State ◽  
Parameter Uncertainties ◽  
Trajectory Tracking Control ◽  
Adaptive Sliding Mode

When the wheeled mobile robot (WMR) is required to perform specific tasks in complex environment, i.e., on the forestry, wet, icy ground or on the sharp corner, wheel skidding and slipping inevitably occur during trajectory tracking. To improve the trajectory tracking performance of WMR under unknown skidding and slipping condition, an adaptive sliding mode controller (ASMC) design approach based on the extended state observer (ESO) is presented. The skidding and slipping is regarded as external disturbance. In this paper, the ESO is introduced to estimate the lumped disturbance containing the unknown skidding and slipping, parameter variation, parameter uncertainties, etc. By designing a sliding surface based on the disturbance estimation, an adaptive sliding mode tracking control strategy is developed to attenuate the lumped disturbance. Simulation results show that higher precision tracking and better disturbance rejection of ESO-ASMC is realized for linear and circular trajectory than the ASMC scheme. Besides, experimental results indicate the ESO-ASMC scheme is feasible and effective. Therefore, ESO-ASMC scheme can enhance the energy efficiency for the differentially driven WMR under unknown skidding and slipping condition.

A New Neural Network Based Sliding Mode Adaptive Controller for Tracking Control of Robot Manipulator

2021 ◽  
Vol 11 (2) ◽  
pp. 12-16
Author(s):  
Monisha Pathak ◽  
◽  
Mrinal Buragohain ◽  
Keyword(s):  
Neural Network ◽  
Trajectory Tracking ◽  
Tracking Control ◽  
Sliding Mode ◽  
Robot Manipulator ◽  
Rbf Neural Network ◽  
Adaptive Controller ◽  
Robotic Manipulator ◽  
Trajectory Tracking Control ◽  
Chattering Effect

In this paper a New RBF Neural Network based Sliding Mode Adaptive Controller (NNNSMAC) for Robot Manipulator trajectory tracking in the presence of uncertainties and disturbances is introduced. The research offers a learning with minimal parameter (LMP) technique for robotic manipulator trajectory tracking. The technique decreases the online adaptive parameters number in the RBF Neural Network to only one, lowering computational costs and boosting real-time performance. The RBFNN analyses the system's hidden non-linearities, and its weight value parameters are updated online using adaptive laws to control the nonlinear system's output to track a specific trajectory. The RBF model is used to create a Lyapunov function-based adaptive control law. The effectiveness of the designed NNNSMAC is demonstrated by simulation results of trajectory tracking control of a 2 dof Robotic Manipulator. The chattering effect has been significantly reduced.

Attitude trajectory tracking of quadrotor UAV using super-twisting observer-based adaptive controller

2020 ◽  
pp. 095441002096647
Author(s):  
Ai-Jun Chen ◽  
Ming-Jian Sun ◽  
Zhen-Hua Wang ◽  
Nai-Zhang Feng ◽  
Yi Shen
Keyword(s):  
Trajectory Tracking ◽  
Sliding Mode ◽  
Numerical Study ◽  
Adaptive Controller ◽  
Successful Implementation ◽  
Trajectory Tracking Control ◽  
Decision Algorithm ◽  
Chattering Effect ◽  
High Level ◽  
Twisting Algorithm

The successful implementation of high-level decision algorithm on quadrotor depends on the accurate trajectory tracking performance. In this paper attitude estimation and trajectory tracking control problem of quadrotor unmanned aerial vehicle (UAV) with endogenous and exogenous disturbance are considered, where the lumped disturbance characteristic does not have a probabilistic illustration but instead the dynamics are known to have a bound. The problem is handled by developing disturbance estimator and control strategy. In order to estimate lumped disturbance precisely, a globally finite time stable extended state observer is proposed based on super-twisting algorithm. Stability analysis and observer’s parameters selection rule are discussed by using Lyapunov’s stability theory. The proposed observer strategy achieves accurate observing performance of disturbance without increasing observer’s order, and chattering effect is also reduced by applying super-twisting algorithm. Furthermore, a super-twisting sliding mode control law is proposed to guarantee the asymptotic convergence of the drone’s orientation with respect to the reference. Finally, a numerical study based on simulations is presented to analyze the performance of proposed approach.

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