scholarly journals A Robust State Feedback Adaptive Controller with Improved Transient Tracking Error Bounds for Plants with Unknown Varying Control Gain

10.5772/36096 ◽  
2012 ◽  
Author(s):  
A. Rincon ◽  
F. Angulo ◽  
G. Osorio
Keyword(s):  
Error Bounds ◽  
State Feedback ◽  
Tracking Error ◽  
Adaptive Controller ◽  
Control Gain

scholarly journals An Improved Robust Adaptive Controller for a Fed-Batch Bioreactor with Input Saturation and Unknown Varying Control Gain via Dead-Zone Quadratic Forms

Computation ◽  
2021 ◽  
Vol 9 (9) ◽  
pp. 100
Author(s):  
Alejandro Rincón ◽  
Gloria María Restrepo ◽  
Óscar J. Sánchez
Keyword(s):  
Distinctive Feature ◽  
Quadratic Forms ◽  
Dead Zone ◽  
Tracking Error ◽  
Input Saturation ◽  
Adaptive Controller ◽  
Fed Batch ◽  
Batch Bioreactor ◽  
Control Gain ◽  
Robust Adaptive

In this work, a new adaptive controller is designed for substrate control of a fed-batch bioreactor in the presence of input saturation and unknown varying control gain with unknown upper and lower bounds. The output measurement noise and the unknown varying nature of reaction rate and biomass concentration and water volume are also handled. The design is based on dead zone quadratic forms. The designed controller ensures the convergence of the modified tracking error and the boundedness of the updated parameters. As the first distinctive feature, a new robust adaptive auxiliary system is proposed in order to tackle input saturation and control gain uncertainty. As the second distinctive feature, the modified tracking error converges to a compact region whose bound is user-defined, in contrast to related studies where the convergence region depends on upper bounds of either external disturbances, system states, model parameters or terms and model parameter values. Simulations confirm the properties of the closed loop behavior.

Adaptive State Feedback to Maximize the Power Capture and Reduce the Tower Motion of Wind Turbine in Partial Loading Operation

2015 ◽  
Author(s):  
Kaman Thapa Magar ◽  
Mark J. Balas
Keyword(s):  
Wind Speed ◽  
Wind Turbine ◽  
State Feedback ◽  
Tracking Error ◽  
Adaptive Controller ◽  
Stability And Convergence ◽  
Speed Ratio ◽  
Rotor Speed ◽  
Control Approach ◽  
Tip Speed Ratio

A direct adaptive control approach is used to track the tip speed ratio of wind turbine to maximize the power captured during the below rated wind speed operation. Assuming a known optimum value of tip speed ratio, the deviation of actual tip speed ratio from the optimum one is mathematically expressed as tip speed ratio tracking error. Since the actual tip speed ratio is not a measurable quantity, this expression for tip speed ratio tracking error is linearized and simplified to express it in terms of wind speed and rotor speed, where rotor speed can easily be measured whereas an estimator is designed to estimate the wind speed. Important results from stability and convergence analysis of the proposed adaptive controller with state estimation and state feedback is also presented. From the analysis it was observed that the adaptive disturbance tracking controller can be combined with adaptive state feedback to achieve other control objectives such as reducing the wind turbine structural loading. Hence, an adaptive state feedback scheme is also proposed to reduce wind turbine tower fore-aft and side-side motions.

Adaptive Augmenting Control Design for Time-Varying Polytopic Systems

2016 ◽  
Vol 139 (1) ◽  
Author(s):  
Hessam Mahdianfar ◽  
Emmanuel Prempain
Keyword(s):  
Convex Optimization ◽  
State Feedback ◽  
Closed Loop ◽  
Reference Model ◽  
Tracking Error ◽  
Control Design ◽  
Adaptive Controller ◽  
Time Varying ◽  
Robust Convex Optimization ◽  
And Performance

To increase the performance of closed-loop controlled systems in off-nominal conditions and in the presence of inevitable faults and uncertainties, a systematic approach based on robust convex optimization for adaptive augmenting control design is discussed in this paper. More specifically, this paper addresses the problem of adaptive augmenting controller (AAC) design for systems with time-varying polytopic uncertainty. First, a robust state-feedback controller is designed via robust convex optimization as a baseline controller. The closed-loop polytopic system with the baseline controller is considered as the desired time-varying reference model for the design of a direct state-feedback adaptive controller. Next using Lyapunov arguments, global stability of combined robust baseline and adaptive augmenting controllers is established. Furthermore, it is proved that tracking error converges to zero asymptotically. A case study for a generic nonminimum phase nonlinear pitch-axis missile autopilot is conducted. Simulation tests are performed to evaluate stability and performance of nonlinear time-varying closed-loop system in the presence of uncertainties in pitching moment and normal force coefficients, and unmodeled time delays. In addition, results of the simulations indicate satisfactory robustness in case of severe loss of control effectiveness event.

Iterative learning control algorithm for sensor fault nonlinear systems

2020 ◽  
pp. 1-8
Author(s):  
Zimian Lan
Keyword(s):  
Nonlinear Systems ◽  
Iterative Learning Control ◽  
Control Algorithm ◽  
Tracking Error ◽  
Learning Control ◽  
Open Loop ◽  
Iterative Learning ◽  
Sensor Fault ◽  
Initial State ◽  
Control Gain

In this paper, we propose a new iterative learning control algorithm for sensor faults in nonlinear systems. The algorithm does not depend on the initial value of the system and is combined with the open-loop D-type iterative learning law. We design a period that shortens as the number of iterations increases. During this period, the controller corrects the state deviation, so that the system tracking error converges to the boundary unrelated to the initial state error, which is determined only by the system’s uncertainty and interference. Furthermore, based on the λ norm theory, the appropriate control gain is selected to suppress the tracking error caused by the sensor fault, and the uniform convergence of the control algorithm and the boundedness of the error are proved. The simulation results of the speed control of the injection molding machine system verify the effectiveness of the algorithm.

scholarly journals Fuzzy Adaptive Prescribed Performance Control for Uncertain Horizontal Platform System with Unknown Control Gain

2015 ◽  
Vol 2015 ◽  
pp. 1-8
Author(s):  
Wei Xiang ◽  
Yeguo Sun ◽  
Chunzhi Yang
Keyword(s):  
Control Method ◽  
Adaptive Controller ◽  
Performance Bounds ◽  
Constrained System ◽  
Prescribed Performance ◽  
Performance Technique ◽  
Control Gain ◽  
Unknown Control ◽  
Platform System ◽  
Fuzzy Adaptive

This paper proposes a fuzzy adaptive control method for uncertain horizontal platform system with unknown control gain, which is capable of guaranteeing the prescribed performance bounds. An error transformation is introduced to transform the original constrained system into an equivalent unconstrained one. Then, based on the error transformation technique and the predefined performance technique, a fuzzy adaptive controller is designed for the unconstrained system. It is shown that all the variables of the resulting closed-loop system are bounded. Finally, an illustrative example is given to demonstrate the effectiveness and usefulness of the proposed method.

scholarly journals Adaptive Control for a Biological Process under Input Saturation and Unknown Control Gain via Dead Zone Lyapunov Functions

2020 ◽  
Vol 11 (1) ◽  
pp. 251
Author(s):  
Alejandro Rincón ◽  
Fredy E. Hoyos ◽  
John E. Candelo-Becerra
Keyword(s):  
Lower Bounds ◽  
Distinctive Feature ◽  
Biological Process ◽  
Dead Zone ◽  
Tracking Error ◽  
Input Saturation ◽  
Auxiliary System ◽  
Upper And Lower Bounds ◽  
Compact Set ◽  
Control Gain

In this work, substrate control of a biological process with unknown varying control gain, input saturation, and uncertain reaction rate is addressed. A novel adaptive controller is proposed, which tackles the combined effect of input saturation and unknown varying control gain with unknown upper and lower bounds. The design is based on dead zone radially unbounded Lyapunov-like functions, with the state backstepping as control framework. The convergence of the modified tracking error and the boundedness of the updated parameters are ensured by means of the Barbalat’s lemma. As the first distinctive feature, a new second-order auxiliary system is proposed that tackles the effect of saturated input and the unknown varying control gain with unknown upper and lower bounds. As the second distinctive feature, the modified tracking error converges to a compact set whose width is user-defined, so that it does not depend on bounds of either external disturbances, model terms, or model coefficients. The convergence region of the current tracking error is determined for the closed loop system subject to the formulated controller and the proposed auxiliary system. Finally, numerical simulation illustrates the performance of the proposed controller.

scholarly journals Data-Driven Model-Free Adaptive Control of Z-Source Inverters

Sensors ◽  
2021 ◽  
Vol 21 (22) ◽  
pp. 7438
Author(s):  
Yasin Asadi ◽  
Amirhossein Ahmadi ◽  
Sasan Mohammadi ◽  
Ali Moradi Amani ◽  
Mousa Marzband ◽  
...  
Keyword(s):  
State Feedback ◽  
Adaptive Controller ◽  
Green Energy ◽  
Data Driven ◽  
Control Action ◽  
Linear Quadratic ◽  
Model Based ◽  
Model Free ◽  
Quadratic Integral ◽  
Lyapunov Sense

The universal paradigm shift towards green energy has accelerated the development of modern algorithms and technologies, among them converters such as Z-Source Inverters (ZSI) are playing an important role. ZSIs are single-stage inverters which are capable of performing both buck and boost operations through an impedance network that enables the shoot-through state. Despite all advantages, these inverters are associated with the non-minimum phase feature imposing heavy restrictions on their closed-loop response. Moreover, uncertainties such as parameter perturbation, unmodeled dynamics, and load disturbances may degrade their performance or even lead to instability, especially when model-based controllers are applied. To tackle these issues, a data-driven model-free adaptive controller is proposed in this paper which guarantees stability and the desired performance of the inverter in the presence of uncertainties. It performs the control action in two steps: First, a model of the system is updated using the current input and output signals of the system. Based on this updated model, the control action is re-tuned to achieve the desired performance. The convergence and stability of the proposed control system are proved in the Lyapunov sense. Experiments corroborate the effectiveness and superiority of the presented method over model-based controllers including PI, state feedback, and optimal robust linear quadratic integral controllers in terms of various metrics.

Tracking error bounds of adaptive nonstationary filtering

Automatica ◽  
1985 ◽  
Vol 21 (3) ◽  
pp. 293-302 ◽  
Author(s):  
Eweda Eweda ◽  
Odile Macchi
Keyword(s):  
Error Bounds ◽  
Tracking Error

ROBUST ADAPTIVE FUZZY TRACKING CONTROL FOR A CLASS OF PERTURBED UNCERTAIN NONLINEAR SYSTEMS WITH UVCGF

2007 ◽  
Vol 05 (01) ◽  
pp. 227-239 ◽  
Author(s):  
TIESHAN LI ◽  
YANSHENG YANG ◽  
JIANGQIANG HU ◽  
LINJIA YANG
Keyword(s):  
Fuzzy Controller ◽  
A Priori ◽  
Tracking Error ◽  
Closed Loop System ◽  
Uncertain Nonlinear System ◽  
Gain Function ◽  
Singularity Problem ◽  
Adaptive Fuzzy ◽  
Control Gain ◽  
Robust Adaptive

In this paper, a robust adaptive fuzzy controller is presented for a wide class of perturbed uncertain nonlinear system with unknown virtual control gain function (UVCGF). The Mamdani fuzzy system is used to approximate unstructured uncertain functions in the system. The proposed algorithm, which incorporated Nussbaum-type gain into the decoupled backstepping approach, does not require a priori knowledge of the sign of UVCGF, and circumvents the controller-singularity problem gracefully in some existing literatures. It proved that the tracking error can be driven to a small residual set while keeping all signals in the closed-loop system semi-globally uniformly ultimately bounded (SGUUB). Simulation results are presented to validate the effectiveness of the proposed controller.

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