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.

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 A Robust Observer—Based Adaptive Control of Second—Order Systems with Input Saturation via Dead-Zone Lyapunov Functions

Computation ◽  
2021 ◽  
Vol 9 (8) ◽  
pp. 82
Author(s):  
Alejandro Rincón ◽  
Gloria M. Restrepo ◽  
Fredy E. Hoyos
Keyword(s):  
Lyapunov Functions ◽  
Dead Zone ◽  
Tracking Error ◽  
Input Saturation ◽  
Chemical Reactor ◽  
Second Order ◽  
Control Law ◽  
Compact Set ◽  
State Variables ◽  
Robust Observer

In this study, a novel robust observer-based adaptive controller was formulated for systems represented by second-order input–output dynamics with unknown second state, and it was applied to concentration tracking in a chemical reactor. By using dead-zone Lyapunov functions and adaptive backstepping method, an improved control law was derived, exhibiting faster response to changes in the output tracking error while avoiding input chattering and providing robustness to uncertain model terms. Moreover, a state observer was formulated for estimating the unknown state. The main contributions with respect to closely related designs are (i) the control law, the update law and the observer equations involve no discontinuous signals; (ii) it is guaranteed that the developed controller leads to the convergence of the tracking error to a compact set whose width is user-defined, and it does not depend on upper bounds of model terms, state variables or disturbances; and (iii) the control law exhibits a fast response to changes in the tracking error, whereas the control effort can be reduced through the controller parameters. Finally, the effectiveness of the developed controller is illustrated by the simulation of concentration tracking in a stirred chemical reactor.

Robust Adaptive Controller for the Diesel Engine Air Path with Input Saturation

2019 ◽  
Vol 17 (10) ◽  
pp. 2541-2549 ◽  
Author(s):  
Samia Larguech ◽  
Sinda Aloui ◽  
Olivier Pagès ◽  
Ahmed El Hajjaji ◽  
Abdessattar Chaari
Keyword(s):  
Diesel Engine ◽  
Input Saturation ◽  
Adaptive Controller ◽  
Robust Adaptive ◽  
Robust Adaptive Controller

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.

scholarly journals Neural Network-Based State Estimation for a Closed-Loop Control Strategy Applied to a Fed-Batch Bioreactor

Complexity ◽  
2017 ◽  
Vol 2017 ◽  
pp. 1-16 ◽  
Author(s):  
Santiago Rómoli ◽  
Mario Serrano ◽  
Francisco Rossomando ◽  
Jorge Vega ◽  
Oscar Ortiz ◽  
...  
Keyword(s):  
Neural Network ◽  
Closed Loop ◽  
Rbf Neural Network ◽  
Control Strategies ◽  
Tracking Error ◽  
Closed Loop Control ◽  
Online Information ◽  
Fed Batch ◽  
Loop Control ◽  
Batch Bioreactor

The lack of online information on some bioprocess variables and the presence of model and parametric uncertainties pose significant challenges to the design of efficient closed-loop control strategies. To address this issue, this work proposes an online state estimator based on a Radial Basis Function (RBF) neural network that operates in closed loop together with a control law derived on a linear algebra-based design strategy. The proposed methodology is applied to a class of nonlinear systems with three types of uncertainties: (i) time-varying parameters, (ii) uncertain nonlinearities, and (iii) unmodeled dynamics. To reduce the effect of uncertainties on the bioreactor, some integrators of the tracking error are introduced, which in turn allow the derivation of the proper control actions. This new control scheme guarantees that all signals are uniformly and ultimately bounded, and the tracking error converges to small values. The effectiveness of the proposed approach is illustrated on the basis of simulated experiments on a fed-batch bioreactor, and its performance is compared with two controllers available in the literature.

scholarly journals Adaptive NN Control for Multisteering Plane Aircraft with Dead Zone or Backlash Input Nonlinearity

2017 ◽  
Vol 2017 ◽  
pp. 1-8 ◽  
Author(s):  
Xiang-fei Meng ◽  
Ying Wang ◽  
Mao-long Lv
Keyword(s):  
Neural Network ◽  
Dead Zone ◽  
External Disturbance ◽  
Tracking Error ◽  
Network Control ◽  
Control Allocation ◽  
Input Nonlinearity ◽  
Adaptive Neural Network Control ◽  
Robust Adaptive ◽  
Backlash Nonlinearity

Considering that many factors such as actuator input dead zone, backlash, and external disturbance could affect the exactness of trajectory tracking, therewith a robust adaptive neural network control scheme on the basis of control allocation is proposed for the sake of tracking control of multisteering plane aircraft with actuator input dead zone or backlash nonlinearity. First of all, an actuator input dead zone or backlash nonlinearity control assignment model is established and the control allocation equation is derived. Secondly, the system nonlinear uncertainty is compensated by means of radial basis function neural network, and a robust term is introduced to achieve robustness against external disturbance and system errors. Finally, by utilizing Lyapunov stability theorem, it has been proved that all the signals in the closed-loop system are bounded, and the tracking error converges to a small residual set asymptotically. Simulation results on ICE101 multisteering plane aircraft demonstrate the outstanding tracking performance and strong robustness as well as effectiveness of the proposed approach, which can effectively overcome the adverse influence of dead zone, backlash nonlinearity, and external disturbance on the system.

scholarly journals Neural Networks Approximator Based Robust Adaptive Controller Design of Hypersonic Flight Vehicles Systems Coupled with Stochastic Disturbance and Dynamic Uncertainties

2017 ◽  
Vol 2017 ◽  
pp. 1-10 ◽  
Author(s):  
Guoqiang Zhu ◽  
Lingfang Sun ◽  
Xiuyu Zhang
Keyword(s):  
Controller Design ◽  
Tracking Error ◽  
Adaptive Controller ◽  
Stochastic Disturbance ◽  
Hypersonic Flight ◽  
Flight Vehicles ◽  
Uncertain Dynamics ◽  
Robust Adaptive ◽  
And Performance ◽  
Dynamic Uncertainties

A neural network robust control is proposed for a class of generic hypersonic flight vehicles with uncertain dynamics and stochastic disturbance. Compared with the present schemes of dealing with dynamic uncertainties and stochastic disturbance, the outstanding feature of the proposed scheme is that only one parameter needs to be estimated at each design step, so that the computational burden can be greatly reduced and the designed controller is much simpler. Moreover, by introducing a performance function in controller design, the prespecified transient and performance of tracking error can be guaranteed. It is proved that all signals of closed-loop system are uniformly ultimately bounded. The simulation results are carried out to illustrate effectiveness of the proposed control algorithm.

Robust adaptive finite-time tracking control of uncertain mechanical systems with input saturation and deadzone

2018 ◽  
Vol 41 (2) ◽  
pp. 560-572 ◽  
Author(s):  
Baofang Wang ◽  
Sheng Li ◽  
Qingwei Chen
Keyword(s):  
Finite Time ◽  
Tracking Control ◽  
Design Method ◽  
Tracking Error ◽  
Input Saturation ◽  
Mechanical Systems ◽  
Lyapunov Stability Theory ◽  
Continuous Functions ◽  
Model Uncertainties ◽  
Robust Adaptive

This paper addresses the problem of robust adaptive finite-time tracking control for a class of mechanical systems in the presence of model uncertainties, unknown external disturbances, and input nonlinearities containing saturation and deadzone. Without imposing any conditions on the model uncertainties, radial basis function neural networks are used to approximate unknown nonlinear continuous functions, and an adaptive tracking control scheme is proposed by exploiting the recursive design method. It is shown that the input saturation and deadzone model can be expressed as a simple linear system with a time-varying gain and bounded disturbance. An adaptive compensation term for the upper bound of the lumped disturbance is introduced. The semi-global finite-time uniform ultimate boundedness of the corresponding closed-loop tracking error system is proved with the help of the finite-time Lyapunov stability theory. Finally, an example is given to demonstrate the effectiveness of the proposed method.

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