scholarly journals Adaptive Asymptotic Tracking Control for a Class of Uncertain Switched Systems via Dynamic Surface Technique

Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-9
Author(s):  
Xuemiao Chen ◽  
Qianjin Zhao ◽  
Chunsheng Zhang ◽  
Jian Wu
Keyword(s):  
Switched Systems ◽  
Tracking Control ◽  
Control Method ◽  
Reference Signal ◽  
Adaptive Controller ◽  
Dynamic Surface Control ◽  
Dynamic Surface ◽  
Adaptive Tracking Control ◽  
Nonlinear Switched Systems ◽  
Control Scheme

A novel adaptive tracking control scheme is proposed for a class of uncertain nonlinear switched systems with perturbations in this paper. The common Lyapunov function method is introduced to handle the switched system in the design process of the desired adaptive controller. In addition, a dynamic surface control method is proposed by employing a nonlinear filter such that the “explosion of complexity” problem existing in the conventional backstepping design can be overcome. Under the presented adaptive controller, all the closed-loop signals are semiglobally bounded, and especially the output signal of the controlled system can follow the given reference signal asymptotically. To show the availability of the presented control scheme, a simulation is given in this paper.

Adaptive Tracking Control of Industrial Robots

1988 ◽  
Vol 110 (3) ◽  
pp. 215-220 ◽  
Author(s):  
G. Ambrosino ◽  
G. Celentano ◽  
F. Garofalo
Keyword(s):  
Input Signal ◽  
Tracking Control ◽  
Design Procedure ◽  
Adaptive Controller ◽  
Approximate Model ◽  
Industrial Robots ◽  
Uncertain Parameters ◽  
Load Variations ◽  
Adaptive Tracking Control ◽  
Control Scheme

A design procedure for the synthesis of an adaptive controller for a robotic manipulator is presented. The design involves the evaluation of a nominal input signal by using a model of the manipulator with nominal values of the loads, and of an adaptive component by means of the sole knowledge of the maximum possible size of the uncertain parameters of the model. The proposed control scheme also guarantees an accurate tracking of a planned path when an approximate model of the manipulator is used and/or load variations occur during operation. Moreover, the resulting control signal is smooth.

scholarly journals On Stability of Perturbed Nonlinear Switched Systems with Adaptive Reinforcement Learning

Energies ◽  
2020 ◽  
Vol 13 (19) ◽  
pp. 5069
Author(s):  
Phuong Nam Dao ◽  
Hong Quang Nguyen ◽  
Minh-Duc Ngo ◽  
Seon-Ju Ahn
Keyword(s):  
Optimal Control ◽  
Reinforcement Learning ◽  
Switched Systems ◽  
Tracking Control ◽  
Control Method ◽  
Learning Algorithm ◽  
Hjb Equation ◽  
Control Approach ◽  
Nonlinear Switched Systems ◽  
Hamilton Jacobi Bellman

In this paper, a tracking control approach is developed based on an adaptive reinforcement learning algorithm with a bounded cost function for perturbed nonlinear switched systems, which represent a useful framework for modelling these converters, such as DC–DC converter, multi-level converter, etc. An optimal control method is derived for nominal systems to solve the tracking control problem, which results in solving a Hamilton–Jacobi–Bellman (HJB) equation. It is shown that the optimal controller obtained by solving the HJB equation can stabilize the perturbed nonlinear switched systems. To develop a solution to the translated HJB equation, the proposed neural networks consider the training technique obtaining the minimization of square of Bellman residual error in critic term due to the description of Hamilton function. Theoretical analysis shows that all the closed-loop system signals are uniformly ultimately bounded (UUB) and the proposed controller converges to optimal control law. The simulation results of two situations demonstrate the effectiveness of the proposed controller.

Attitude and height tracking control of unmanned helicopters with disturbances via disturbance observer-based composite dynamic surface control

2021 ◽  
pp. 014233122110232
Author(s):  
Xiangyu Wang ◽  
Ling Han ◽  
Jiyu Liu
Keyword(s):  
Tracking Control ◽  
Disturbance Observer ◽  
Control Design ◽  
Dynamic Surface Control ◽  
Control Technique ◽  
Tracking Errors ◽  
Dynamic Surface ◽  
Surface Control ◽  
Control Scheme ◽  
Tracking Controller

In this paper, the attitude and height tracking control problem is studied for unmanned helicopters with disturbances. To solve the problem, a composite control scheme is proposed based on the combination of dynamic surface control and disturbance observer-based control techniques. The control design includes two parts. In the first part, some nonlinear disturbance observers are designed to accurately estimate the helicopter’s disturbances in different channels. In the second part, based on the disturbance estimates and dynamic surface control technique, a composite dynamic surface tracking controller is designed. Under the proposed composite controller, the attitude and height tracking errors are uniformly ultimately bounded and they can be regulated to be very small by selecting proper controller parameters. For one thing, the proposed control scheme avoids “explosion of terms”, which generally exists in conventional backstepping control and provides a simpler control design. For another thing, without sacrificing the nominal control performances, the anti-disturbance ability of the closed-loop helicopter system is enhanced by using disturbance observers and feedforward compensations. Numerical simulations demonstrate the effectiveness and advantages of the proposed composite tracking controller.

scholarly journals Adaptive Asymptotic Tracking Control for a Class of Uncertain Input-Delayed Systems with Periodic Time-Varying Disturbances

2021 ◽  
Vol 2021 ◽  
pp. 1-21
Author(s):  
Xiaoman Yan ◽  
Chunsheng Zhang ◽  
Dewen Cao ◽  
Jian Wu
Keyword(s):  
Tracking Control ◽  
Reference Signal ◽  
Dynamic Surface Control ◽  
Control Technique ◽  
Fourier Series Expansion ◽  
Time Varying ◽  
Dynamic Surface ◽  
Delayed Systems ◽  
Asymptotic Tracking ◽  
Function Approximator

In this paper, the problem of adaptive asymptotic tracking control for a class of uncertain systems with periodic time-varying disturbances and input delay is studied. By combining Fourier series expansion (FSE) with radial basis function neural network (RBFNN), a hybrid function approximator is used to learn the functions with periodic time-varying disturbances. At the same time, the dynamic surface control technique with a nonlinear filter is used to avoid the “complexity explosion” problem in the process of traditional backstepping technology. Ultimately, all closed-loop signals are guaranteed to be semiglobally uniformly bounded, and the given reference signal can be asymptotically tracked by the output signals of system. A simulation example is given to verify the effectiveness of the proposed control scheme.

scholarly journals ADAPTIVE TRACKING CONTROL FOR TWIN ROTOR MULTIPLE-INPUT MULTIPLE-OUTPUT BASED ON ISS STABILIZATION

2016 ◽  
Vol 54 (5) ◽  
pp. 672
Author(s):  
Nguyen Van Chi
Keyword(s):  
Tracking Control ◽  
Control Method ◽  
Multiple Input Multiple Output ◽  
Adaptive Controller ◽  
Uncertain Parameters ◽  
Vertical Movements ◽  
Adaptive Tracking Control ◽  
Input Multiple Output ◽  
Cable Force ◽  
Twin Rotor

This paper proposes the angle tracking control method for Twin rotor multi-input multiple-output (TRMS) using the input-to-state stability theory (ISS) for nonlinear systems. To apply this theory, the model of TRMS is rewritten by an Euler-Lagrange forced model with uncertain parameters and input disturbances. The uncertain parameters are the potential energies depended on the mass of TRMS’parts and the input disturbances are considered the friction force, the flat cable force, the effects of the speed of the main rotor on the horizontal movement and the speed of tail rotor to the vertical movements. Using modificated model of TRMS, we design the adaptive controller for angle ISS stabilization to attenuate the influences of uncertain parameters and input disturbances to the angles of TRMS. The robustness of the closed system is shown by the the stabilization of the angles with the yaw and pitch external disturbances, the simulation and experimental results help to proof the rightness of proposed method.

scholarly journals Robust Tracking Control for Vehicle Lateral Dynamics with Uncertain Parameters and External Nonlinearities

2014 ◽  
Vol 2014 ◽  
pp. 1-12 ◽  
Author(s):  
Huihui Pan ◽  
Yifu Zhang ◽  
Weichao Sun
Keyword(s):  
Tracking Control ◽  
Controller Design ◽  
Reference Signal ◽  
Dynamic Surface Control ◽  
Parameter Uncertainties ◽  
Robust Tracking Control ◽  
Sideslip Angle ◽  
Dynamic Surface ◽  
Control Laws ◽  
Yaw Rate

This paper focuses on the problem of tracking control for vehicle lateral dynamic systems and designs an adaptive robust controller (ARC) based on backstepping technology to improve vehicle handling and stability, in the presence of parameter uncertainties and external nonlinearities. The main target of controller design has two aspects: the first target is to control the sideslip angle as small as possible, and the second one is to keep the real yaw rate tracking the desired yaw rate. In order to compromise the two indexes, the desired sideslip angle is planned as a new reference signal, instead of the ideal “zero.” As a result, the designed controller not only accomplishes the control purposes mentioned above, but also effectively attenuates both the changes of vehicle mass and the variations of cornering stiffness. In addition, to overcome the problem of “explosion of complexity” caused by backstepping method in the traditional ARC design, the dynamic surface control (DSC) technique is used to estimate the derivative of the virtual control. Finally, a nonlinear vehicle model is employed as the design example to illustrate the effectiveness of the proposed control laws.

scholarly journals Adaptive Tracking Control for a Class of Manipulator Systems with State Constraints and Stochastic Disturbances

2018 ◽  
Vol 2018 ◽  
pp. 1-6
Author(s):  
Wei Sun ◽  
Wenxing Yuan ◽  
Jing Zhang ◽  
Qun Sun
Keyword(s):  
Tracking Control ◽  
Closed Loop ◽  
State Constraints ◽  
Adaptive Controller ◽  
Compact Set ◽  
Closed Loop System ◽  
Stochastic Disturbances ◽  
Adaptive Tracking Control ◽  
Barrier Lyapunov Function ◽  
Control Scheme

An adaptive controller is constructed for a class of stochastic manipulator nonlinear systems in this paper. The states are constrained in the compact set. A tan-type Barrier Lyapunov Function (BLF) is employed to deal with state constraints. The proposed control scheme guarantees the output error convergence to a small neighbourhood of zero. All the signals in the closed-loop system are bounded. The simulation results illustrate the validity of the proposed method.

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