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 Designing the Adaptive Tracking Controller for Uncertain Fully Actuated Dynamical Systems with Additive Disturbances Based on Sliding Mode

2016 ◽  
Vol 2016 ◽  
pp. 1-11
Author(s):  
Chi Nguyen Van
Keyword(s):  
Dynamical Systems ◽  
Tracking Control ◽  
Control Method ◽  
Sliding Mode ◽  
Control Law ◽  
Uncertain Parameters ◽  
Transient Time ◽  
Vertical Movements ◽  
Adaptive Tracking Control ◽  
Adaptive Tracking

This paper addresses the problem of adaptive tracking control for uncertain fully actuated dynamical systems with additive disturbance (FDSA) based on the sliding mode. We use the adaptive mechanism to adjust the uncertain parameters in sliding mode control law which can be switched to two modes depending on the sliding surface. By choosing appropriately the parameters in control law, the desired transient time can be obtained without effects of uncertain parameters and additive disturbances. The chattering phenomenon can be minimized by a chosen constant. This control method is applied to the angles tracking control of the twin rotor multi-input multi-output system (TRMS) which have nonlinear characteristics, the input torque disturbances and the coupling between the horizontal and vertical movements. The simulation and experimental results are presented that validate the proposed solution.

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 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.

Multivariable predictive functional control of a compound power-split hybrid electric vehicle

2021 ◽  
pp. 095440702110466
Author(s):  
Ji Gao ◽  
Diming Lou ◽  
Tong Zhang ◽  
Liang Fang ◽  
Yunhua Zhang
Keyword(s):  
Hybrid System ◽  
Hybrid Electric Vehicle ◽  
Control Method ◽  
Multiple Input Multiple Output ◽  
Area Network ◽  
Control Effect ◽  
Decoupling Method ◽  
Input Multiple Output ◽  
Objective Control ◽  
Pure Delay

The Corun hybrid system (CHS) is a deeply coupled multiple-input–multiple-output (MIMO) hybrid system. The two inputs are the torques of the two motors. The two outputs are the carrier speed and transmission output torque. Using the traditional control method, the multi-objective control quality cannot be guaranteed because of the adopted static decoupling method and proportional–integral–derivative (PID) controllers. In this paper, the problems of the traditional control method are carefully analyzed, and a new control method is proposed. Instead of static decoupling, dynamic decoupling is adopted to improve the decoupling control effect. A predictive functional controller instead of a PID controller is adopted to deal with the pure delay caused by controller area network (CAN) communication. The tracking effect of the target value is further improved by predictive functional controllers. For the two decoupled subsystems, that is, the integral system and the second-order underdamped system, two predictive functional controllers are designed. The new control method was verified by simulations and tests. The results show that the new control method is superior to the traditional control method for CHS.

Adaptive Backstepping Control of the Gripping Process of Heavy Manipulators

2017 ◽  
Author(s):  
Lixin Yang ◽  
Xianmin Zhang
Keyword(s):  
Tracking Control ◽  
Hydraulic Drive ◽  
Adaptive Controller ◽  
Drive System ◽  
Uncertain Parameters ◽  
Backstepping Method ◽  
Nonlinear Characteristics ◽  
Cylinder Model ◽  
Stability Principle ◽  
The Stability

A valve-controlled asymmetrical cylinder model was established to study the gripping hydraulic drive system of the grip device of heavy manipulator. Due to the strong nonlinear characteristics and uncertain parameters of the model, the Lyapunov stability principle was used to design a multistage inversion adaptive controller based on backstepping method and by introducing the virtual control parameter. The simulation results reveal that the tracking control and adaptive of uncertain parameters are very effective, which confirm that the designed controller can guarantee the stability of the closed-loop clamping hydraulic drive system.

scholarly journals Direct Adaptive Tracking Control for a Class of Pure-Feedback Stochastic Nonlinear Systems Based on Fuzzy-Approximation

2014 ◽  
Vol 2014 ◽  
pp. 1-10
Author(s):  
Huanqing Wang ◽  
Xiaoping Liu ◽  
Qi Zhou ◽  
Hamid Reza Karimi
Keyword(s):  
Nonlinear Systems ◽  
Tracking Control ◽  
Controller Design ◽  
Tracking Error ◽  
Small Neighborhood ◽  
Adaptive Controller ◽  
Stochastic Nonlinear Systems ◽  
Fuzzy Logic Systems ◽  
Adaptive Tracking Control ◽  
Adaptive Tracking

The problem of fuzzy-based direct adaptive tracking control is considered for a class of pure-feedback stochastic nonlinear systems. During the controller design, fuzzy logic systems are used to approximate the packaged unknown nonlinearities, and then a novel direct adaptive controller is constructed via backstepping technique. It is shown that the proposed controller guarantees that all the signals in the closed-loop system are bounded in probability and the tracking error eventually converges to a small neighborhood around the origin in the sense of mean quartic value. The main advantages lie in that the proposed controller structure is simpler and only one adaptive parameter needs to be updated online. Simulation results are used to illustrate the effectiveness of the proposed approach.

scholarly journals Neural NetworkL1Adaptive Control of MIMO Systems with Nonlinear Uncertainty

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Hong-tao Zhen ◽  
Xiao-hui Qi ◽  
Jie Li ◽  
Qing-min Tian
Keyword(s):  
Mimo Systems ◽  
Mimo System ◽  
Multiple Input Multiple Output ◽  
Adaptive Controller ◽  
Rbf Neural Networks ◽  
Pass Filter ◽  
Low Pass Filter ◽  
Input Multiple Output ◽  
Low Pass ◽  
Nonlinear Uncertainties

An indirect adaptive controller is developed for a class of multiple-input multiple-output (MIMO) nonlinear systems with unknown uncertainties. This control system is comprised of anL1adaptive controller and an auxiliary neural network (NN) compensation controller. TheL1adaptive controller has guaranteed transient response in addition to stable tracking. In this architecture, a low-pass filter is adopted to guarantee fast adaptive rate without generating high-frequency oscillations in control signals. The auxiliary compensation controller is designed to approximate the unknown nonlinear functions by MIMO RBF neural networks to suppress the influence of uncertainties. NN weights are tuned on-line with no prior training and the project operator ensures the weights bounded. The global stability of the closed-system is derived based on the Lyapunov function. Numerical simulations of an MIMO system coupled with nonlinear uncertainties are used to illustrate the practical potential of our theoretical results.

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