scholarly journals Hierarchical Robust Adaptive Control for Wind Turbines with Actuator Fault

2022 ◽  
pp. 1-8
Author(s):  
Sina Ameli ◽  
Olugbenga Anubi
Keyword(s):  
Wind Turbines ◽  
Tracking Error ◽  
Robust Adaptive Control ◽  
Control Input ◽  
Wind Disturbance ◽  
Rotor Speed ◽  
Low Level ◽  
Robust Adaptive ◽  
Error Dynamics ◽  
High Level

Abstract This paper solves the problem of regulating the rotor speed tracking error for wind turbines in the full-load region by an effective robust-adaptive control strategy. The developed controller compensates for the uncertainty in the control input effectiveness caused by a pitch actuator fault, unmeasurable wind disturbance, and nonlinearity in the model. Wind turbines have multi-layer structures such that the high-level structure is nonlinearly coupled through an aggregation of the low-level control authorities. Hence, the control design is divided into two stages. First, an ℒ2 controller is designed to attenuate the influence of wind disturbance fluctuations on the rotor speed. Then, in the low-level layer, a controller is designed using a proposed adaptation mechanism to compensate for actuator faults. The theoretical results show that the closed-loop equilibrium point of the regulated rotor speed tracking error dynamics in the high level is finite-gain ℒ2 stable, and the closed-loop error dynamics in the low level is globally asymptotically stable. Simulation results show that the developed controller significantly reduces the root-mean- square of the rotor speed error compared to some well-known works, despite the largely fluctuating wind disturbance, and the time-varying uncertainty in the control input effectiveness.

scholarly journals Design of a Robust Adaptive Controller for the Pitch and Torque Control of Wind Turbines

Energies ◽  
2020 ◽  
Vol 13 (5) ◽  
pp. 1195 ◽  
Author(s):  
Srikanth Bashetty ◽  
Joaquin I. Guillamon ◽  
Shanmukha S. Mutnuri ◽  
Selahattin Ozcelik
Keyword(s):  
Adaptive Control ◽  
Wind Speed ◽  
Wind Turbine ◽  
Wind Turbines ◽  
Degrees Of Freedom ◽  
Robust Adaptive Control ◽  
Operating Conditions ◽  
Torque Control ◽  
Rotor Speed ◽  
Robust Adaptive

In this paper, robust adaptive control is designed for pitch and torque control of the wind turbines operating under turbulent wind conditions. The dynamics of the wind turbine are formulated by considering the five degrees of freedom system (rotor angle, gearbox angle, generator angle, flap-wise deflection of the rotor blade, and axial displacement of the nacelle). The controller is designed to maintain the rotor speed, maximize the aerodynamic efficiency of the wind turbine, and reduce the loads due to high wind speeds. Gaussian probability distribution function is used for approximating the wind speed, which is given as the disturbance input to the plant. The adaptive control algorithm is implemented to 2 MW and 5 MW wind turbines to test the robustness of the controller for varying parameters. The simulation is carried out using MATLAB/Simulink for three cases, namely pitch control, torque control, and the combined case. A case study is done to validate the proposed adaptive control using real wind speed data. In all the cases, the results indicate that the rotor speed follows the reference speed and show that the designed controller gives a satisfactory performance under varying operating conditions and parameter variations.

scholarly journals Robust Adaptive Control for a Class of Uncertain Nonlinear Systems with Time-Varying Delay

2013 ◽  
Vol 2013 ◽  
pp. 1-8 ◽  
Author(s):  
Ruliang Wang ◽  
Jie Li ◽  
Shanshan Zhang ◽  
Dongmei Gao ◽  
Huanlong Sun
Keyword(s):  
Neural Control ◽  
Tracking Error ◽  
Robust Adaptive Control ◽  
Delay Systems ◽  
Time Varying ◽  
Triangular Form ◽  
Time Varying Delay ◽  
Robust Adaptive ◽  
Error Dynamics ◽  
Varying Delay

We present adaptive neural control design for a class of perturbed nonlinear MIMO time-varying delay systems in a block-triangular form. Based on a neural controller, it is obtained by constructing a quadratic-type Lyapunov-Krasovskii functional, which efficiently avoids the controller singularity. The proposed control guarantees that all closed-loop signals remain bounded, while the output tracking error dynamics converge to a neighborhood of the desired trajectories. The simulation results demonstrate the effectiveness of the proposed control scheme.

scholarly journals Active Shock Absorber Control Based on Time-Delay Neural Network

Energies ◽  
2020 ◽  
Vol 13 (5) ◽  
pp. 1091
Author(s):  
Alexander Alyukov ◽  
Yuri Rozhdestvenskiy ◽  
Sergei Aliukov
Keyword(s):  
Neural Network ◽  
Time Delay ◽  
Shock Absorber ◽  
Learning Ability ◽  
Control Input ◽  
Low Level ◽  
External Data ◽  
Good Learning ◽  
Suspension Model ◽  
High Level

A controlled suspension usually consists of a high-level and a low-level controller. The purpose the high-level controller is to analyze external data on vehicle conditions and make decisions on the required value of the force on the shock absorber rod, while the purpose of the low-level controller is to ensure the implementation of the desired force value by controlling the actuators. Many works have focused on the design of high-level controllers of active suspensions, in which it is considered that the shock absorber can instantly and absolutely accurately implement a given control input. However, active shock absorbers are complex systems that have hysteresis. In addition, electro-pneumatic and hydraulic elements are often used in the design, which have a long response time and often low accuracy. The application of methods of control theory in such systems is often difficult due to the complexity of constructing their mathematical models. In this article, the authors propose an effective low-level controller for an active shock absorber based on a time-delay neural network. Neural networks in this case show good learning ability. The low-level controller is implemented in a simplified suspension model and the simulation results are presented for a number of typical cases.

Robust Adaptive Control of Nonlinear Systems with Uncertainties

2014 ◽  
Vol 568-570 ◽  
pp. 1108-1112
Author(s):  
Ning Liu ◽  
Yu Sheng Liu ◽  
Qiang Yang
Keyword(s):  
Nonlinear Systems ◽  
Tracking Error ◽  
Robust Adaptive Control ◽  
Design Parameters ◽  
Unmodeled Dynamics ◽  
Time Varying ◽  
Mean Square ◽  
Robust Controller ◽  
The Mean ◽  
Robust Adaptive

This paper proposes a robust adaptive robust controller for nonlinear systems represented by input-output models with unmodeled dynamics. Under the circumstances that the output of the system is bounded, the proposed controller can guarantee that all the variables of the system are bounded in the presence of unmodeled dynamics and time-varying disturbances. The scheme does not need to generate an additional dynamic signal to dominate the effects of the unmodeled dynamics. It is shown that the mean-square tracking error can be made arbitrarily small by choosing some design parameters appropriately.

Adaptive control of a class of non-linear systems preceded by backlash-like hysteresis

2014 ◽  
Vol 24 (5) ◽  
Author(s):  
JIANPING CAI ◽  
LUJUAN SHEN ◽  
FUZHEN WU
Keyword(s):  
Differential Equation ◽  
Adaptive Control ◽  
Linear Systems ◽  
Tracking Error ◽  
Robust Adaptive Control ◽  
Unknown Parameters ◽  
Control Scheme ◽  
Non Linear ◽  
Non Linear Systems ◽  
Robust Adaptive

We consider a class of uncertain non-linear systems preceded by unknown backlash-like hysteresis, which is modelled by a differential equation. We propose a new state feedback robust adaptive control scheme using a backstepping technique and properties of the differential equation. In this control scheme, we construct a new continuous function to design an estimator to estimate the unknown constant parameters and the unknown bound of a ‘disturbance-like’ term. The transient performance of the output tracking error can be guaranteed by the introduction of pre-estimates of the unknown parameters in our controller together with update laws. We do not require bounds on the ‘disturbance-like’ term or unknown system parameters in this scheme. The global stability of the closed-loop system can be proved.

scholarly journals Optimal Robust Adaptive FuzzyH∞Tracking Control without Reaching Phase for Nonlinear System

2013 ◽  
Vol 2013 ◽  
pp. 1-7
Author(s):  
El Mehdi Mellouli ◽  
Siham Massou ◽  
Ismail Boumhidi
Keyword(s):  
Fuzzy Controller ◽  
Tracking Error ◽  
Gain Control ◽  
High Gain ◽  
Control Input ◽  
Optimal Value ◽  
Robust Adaptive ◽  
Indirect Adaptive Fuzzy Controller ◽  
The Stability ◽  
Interval Type

An optimalH∞tracking-based indirect adaptive fuzzy controller for a class of perturbed uncertain affine nonlinear systems without reaching phase is being developed in this paper. First a practical Interval Type-2 (IT2) fuzzy system is used in an adaptive scheme to approximate the system using a nonlinear model and to determine the optimal value of theH∞gain control. Secondly, to eliminate the trade-off betweenH∞tracking performance and high gain at the control input, a modified output tracking error has been used. The stability is ensured through Lyapunov synthesis and the effectiveness of the proposed method is proved and the simulation is also given to illustrate the superiority of the proposed approach.

An Robust Adaptive Control Scheme for Hydraulic Servo Systems

2006 ◽  
Author(s):  
Torben Ole Andersen ◽  
Michael Ryygaard Hansen
Keyword(s):  
Adaptive Control ◽  
Tracking Error ◽  
Adaptive Controller ◽  
Robust Adaptive Control ◽  
Region Of Attraction ◽  
Control Scheme ◽  
Whole Space ◽  
Bounded Disturbances ◽  
Robust Adaptive ◽  
Adaptive Control Scheme

The paper looks into Model Reference Adaptive Control (MRAC) based on a linear plant model with constant or slowly varying parameters. The actual plant is non-linear, of a higher model order, subjected to time-varying bounded disturbances, and the measured values may be corrupted by noise. These problems are explored and the adaptive algorithms are modified to counteract instability mechanisms and for improved robustness with respect to bounded disturbances and non-modeled dynamics. The adaptive controller identifies the dominant dynamics and uses feedforward to provide anticipative actions in tracing task while an adaptive feedback part stabilizes the tracking error dynamics. Also the effects of non-modeled high frequency dynamics and bounded disturbances on stability and performance are analyzed. The adaptive control scheme is robust in the sense that it guarantees the existence of a large region of attraction from which all the trajectories remain bounded. The size of the region of attraction depends on the non-modeled dynamics in such a way that if the non-modeled dynamics is infinitely fast, the region of attraction becomes the whole space. Simulation and experimental results are presented and discussed to demonstrate the strength of the proposed algorithm.

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