scholarly journals Design and Implementation of Novel LMI-Based Iterative Learning Robust Nonlinear Controller

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Saleem Riaz ◽  
Hui Lin ◽  
Farkhanda Afzal ◽  
Ayesha Maqbool
Keyword(s):  
Process Model ◽  
Fault Tolerant ◽  
Discrete Systems ◽  
Coefficient Matrix ◽  
Iterative Learning ◽  
Linear Matrix ◽  
Nonlinear Controller ◽  
Output Tracking Control ◽  
Inequality Theory ◽  
The Stability

An iterative learning robust fault-tolerant control algorithm is proposed for a class of uncertain discrete systems with repeated action with nonlinear and actuator faults. First, by defining an actuator fault coefficient matrix, we convert the iterative learning control system into an equivalent unknown nonlinear repetitive process model. Then, based on the mixed Lyapunov function approach, we describe the stability of the nonlinear repetitive mechanism on time and trial indices and have appropriate conditions for the repeated control system’s stability in terms of linear matrix inequality theory. Through LMI techniques, we have obtained satisfactory results and controller stability, and robustness against fault tolerance is also discussed in detail. Finally, the simulation results of the output tracking control of the two exemplary models verify the effectiveness of the proposed algorithm.

A finite-time H-infinite adaptive fault-tolerant controller considering time delay for flutter suppression of airfoil flutter

2019 ◽  
Vol 234 (2) ◽  
pp. 293-307
Author(s):  
Gao Ming-Zhou ◽  
Chen Xin-Yi ◽  
Han Rong ◽  
Yao Jian-Yong
Keyword(s):  
Finite Time ◽  
Control Method ◽  
Controller Design ◽  
Fault Tolerant ◽  
Linear Matrix ◽  
Control Methods ◽  
Actuator Faults ◽  
Control Delay ◽  
Modeling Uncertainties ◽  
The Stability

To suppress airfoil flutter, a lot of control methods have been proposed, such as classical control methods and optimal control methods. However, these methods did not consider the influence of actuator faults and control delay. This paper proposes a new finite-time H∞ adaptive fault-tolerant flutter controller by radial basis function neural network technology and adaptive fault-tolerant control method, taking into account actuator faults, control delay, modeling uncertainties, and external disturbances. The theoretic section of this paper is about airfoil flutter dynamic modeling and adaptive fault-tolerant controller design. Lyapunov function and linear matrix inequality are employed to prove the stability of the proposed control method of this paper. The numeral simulation section further proves the effectiveness and robustness of the proposed control algorithm of this paper.

scholarly journals Fault-tolerant control system for the formation of carbon products

2021 ◽  
pp. 22-29
Author(s):  
Liudmyla Zhuchenko
Keyword(s):  
Control System ◽  
Linear Matrix Inequalities ◽  
Control Method ◽  
Fault Tolerant ◽  
Fault Tolerant Control ◽  
Iterative Learning ◽  
Linear Matrix ◽  
Matrix Inequalities ◽  
Unknown Disturbances ◽  
Cyclic Processes

The production of carbon products is largely resource- and energy-intensive. That is why increasing the efficiency of this production is an urgent scientific and practical task, especially in modern conditions of constant growth of energy costs. An effective way to solve this problem is to create a modern process control system, taking into account possible failures of system components. A method for the synthesis of a fault-tolerant control system for the cyclic formation of carbon products has been developed, which takes into account control errors that are caused by malfunctions of controllers under conditions of unknown disturbances. According to the cyclic nature of the technological process under consideration, a control method with iterative learning was used in the synthesis of the control system. This method considers cyclic processes based on a two-dimensional model (2D model). The proposed control algorithm ensures the convergence of the control process with the task both in time and in each work cycle in order to promote the required quality of control even in the event of unknown disturbances and errors in the performance of controllers. The synthesis of the control system is based on the solution of a system of linear matrix inequalities. Based on the combination of a control method with iterative learning and a control method that takes into account failures in controllers, a method of constructing a fault-tolerant control system for the cyclic formation of carbon products has been synthesized to ensure acceptable operation of the control object in abnormal conditions. The control system has been synthesized by solving a system of linear matrix inequalities with the MATLAB software. In the future, it is necessary to consider optimal settings of the proposed control system and examine its effectiveness in comparison with conventional fault-tolerant systems for non-cyclic processes.

scholarly journals Convergence Analysis of Iterative Learning Control for Two Classes of 2-D Linear Discrete Fornasini–Marchesini Model

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Kai Wan
Keyword(s):  
Convergence Analysis ◽  
Iterative Learning Control ◽  
Three Dimensional ◽  
Discrete Systems ◽  
Learning Control ◽  
Iterative Learning ◽  
Linear Matrix ◽  
Direct Transmission ◽  
Learning Gain ◽  
Linear Discrete Systems

This paper first investigates convergent property of two iterative learning control (ILC) laws for two kinds of two-dimensional linear discrete systems described by the first Fornasini–Marchesini model (2-D LDFFM with a direct transmission from inputs to outputs and 2-D LDFFM with input delay). Different from existing ILC results for 2-D LDFFM, this paper provides convergence analysis in a three-dimensional (3-D) framework. By using row scanning approach (RSA) or column scanning approach (CSA), it is theoretically proved no matter which method is adopted, perfect tracking on the desired reference surface is accomplished. In addition, linear matrix inequality (LMI) technique is utilized to computer the learning gain of the ILC controller. The effectiveness and feasibility of the designed ILC law are illustrated through numerical simulation on a practical thermal process.

scholarly journals PD-Type Iterative Learning Control for Uncertain Spatially Interconnected Systems

Mathematics ◽  
2020 ◽  
Vol 8 (9) ◽  
pp. 1528
Author(s):  
Longhui Zhou ◽  
Hongfeng Tao ◽  
Wojciech Paszke ◽  
Vladimir Stojanovic ◽  
Huizhong Yang
Keyword(s):  
Iterative Learning Control ◽  
Process Model ◽  
Singular System ◽  
Learning Control ◽  
Iterative Learning ◽  
Interconnected Systems ◽  
Space Model ◽  
Repetitive Process ◽  
Spatially Interconnected Systems ◽  
The Stability

This paper puts forward a PD-type iterative learning control algorithm for a class of discrete spatially interconnected systems with unstructured uncertainty. By lifting and changing the variable of discrete space model, the uncertain spatially interconnected systems is converted into equivalent singular system, and the general state space model is derived in view of singular system theory. Then, the state error and output error information are used to design the iterative learning control law, transforming the controlled system into an equivalent repetitive process model. Based on the stability theory of repetitive process, sufficient condition for the stability of the system along the trial is given in the form of linear matrix inequalities (LMIs). Finally, the effectiveness of the proposed algorithm is verified by the simulation of ladder circuits.

scholarly journals Integrated Fault Estimation and Fault-Tolerant Control for Dynamic Positioning of Ships

2019 ◽  
Vol 2019 ◽  
pp. 1-15
Author(s):  
Xiaogong Lin ◽  
Heng Li ◽  
Anzuo Jiang ◽  
Juan Li
Keyword(s):  
Fault Tolerant ◽  
Fault Tolerant Control ◽  
Matching Condition ◽  
High Gain ◽  
Iterative Learning ◽  
Fault Estimation ◽  
Linear Matrix ◽  
Dynamic Positioning ◽  
Control Scheme ◽  
Observer Matching Condition

An integrated fault estimation and fault-tolerant control scheme is developed in this paper for dynamic positioning of ships in the presence of an actuator fault. First, an auxiliary derivative output of dynamic positioning ships is constructed in order to satisfy the so-called observer matching condition, and a high-gain observer is designed to exactly estimate the auxiliary derivative outputs. Then, a fault-tolerant controller is developed for dynamic positioning ships based on the iterative learning observer. By means of Lyapunov–Krasovskii stability theory, it is proved that the proposed fault-tolerant controller is able to estimate the total fault effects and states of ships accurately via the iterative learning observer and also to stabilize the closed-loop system. In addition, the parameter design of the proposed fault-tolerant control system can be conveniently solved in terms of linear matrix inequalities. Finally, simulation studies for dynamic positioning ships with actuator faults are carried out, and the results validate the effectivity of the proposed fault-tolerant control scheme.

scholarly journals The Nonfragile Controller with Covariance Constraint for Stable Motion of Quadruped Search-Rescue Robot

2014 ◽  
Vol 6 ◽  
pp. 917381 ◽  
Author(s):  
Peng Wang ◽  
Jixiang Li ◽  
Yuan Zhang
Keyword(s):  
Angular Velocity ◽  
Control Method ◽  
Discrete Systems ◽  
Linear Matrix ◽  
Rescue Robot ◽  
Stable Motion ◽  
Motion State ◽  
Adams Simulation ◽  
The Stability ◽  
Nonfragile Control

The problem of a stable motion for the quadruped search-rescue robots is described as a variance constrained uncertainty in the discrete systems. According to the model structure of the quadruped search-rescue robot, the kinematics of the robot is analyzed on the basis of the D- H parameter. Each joint of the robot angular velocity is planned using the Jacobian matrix, because the angular velocity is directly related to the stability of walking based on the ADAMS simulation. The nonfragile control method with the covariance constraint is proposed for the gait motion control of the quadruped search-rescue robot. The motion state feedback controller and the covariance upper bounds can be given by the solutions of the linear matrix inequalities (LMI), which makes the system satisfy the covariance constrain theory. The results given by LMI indicate that the proposed control method is correct and effective.

Enlarging the region of stability in robust model predictive controller based on dual-mode control

2021 ◽  
pp. 014233122110123
Author(s):  
Fatemeh Khani ◽  
Mohammad Haeri
Keyword(s):  
Stability Region ◽  
Linear Matrix ◽  
Input State ◽  
Dual Mode ◽  
Model Predictive Controller ◽  
Mode Control ◽  
Robust Model ◽  
Output Constraints ◽  
Predictive Controller ◽  
The Stability

Industrial processes are inherently nonlinear with input, state, and output constraints. A proper control system should handle these challenging control problems over a large operating region. The robust model predictive controller (RMPC) could be an linear matrix inequality (LMI)-based method that estimates stability region of the closed-loop system as an ellipsoid. This presentation, however, restricts confident application of the controller on systems with large operating regions. In this paper, a dual-mode control strategy is employed to enlarge the stability region in first place and then, trajectory reversing method (TRM) is employed to approximate the stability region more accurately. Finally, the effectiveness of the proposed scheme is illustrated on a continuous stirred tank reactor (CSTR) process.

scholarly journals A Robust Fault-Tolerant Predictive Control for Discrete-Time Linear Systems Subject to Sensor and Actuator Faults

Sensors ◽  
2021 ◽  
Vol 21 (7) ◽  
pp. 2307
Author(s):  
Sofiane Bououden ◽  
Ilyes Boulkaibet ◽  
Mohammed Chadli ◽  
Abdelaziz Abboudi
Keyword(s):  
Model Predictive Control ◽  
Linear Systems ◽  
Predictive Control ◽  
Robust Stability ◽  
Discrete Time ◽  
Fault Tolerant ◽  
Linear Matrix ◽  
Input Constraints ◽  
Actuator Faults ◽  
Time Linear

In this paper, a robust fault-tolerant model predictive control (RFTPC) approach is proposed for discrete-time linear systems subject to sensor and actuator faults, disturbances, and input constraints. In this approach, a virtual observer is first considered to improve the observation accuracy as well as reduce fault effects on the system. Then, a real observer is established based on the proposed virtual observer, since the performance of virtual observers is limited due to the presence of unmeasurable information in the system. Based on the estimated information obtained by the observers, a robust fault-tolerant model predictive control is synthesized and used to control discrete-time systems subject to sensor and actuator faults, disturbances, and input constraints. Additionally, an optimized cost function is employed in the RFTPC design to guarantee robust stability as well as the rejection of bounded disturbances for the discrete-time system with sensor and actuator faults. Furthermore, a linear matrix inequality (LMI) approach is used to propose sufficient stability conditions that ensure and guarantee the robust stability of the whole closed-loop system composed of the states and the estimation error of the system dynamics. As a result, the entire control problem is formulated as an LMI problem, and the gains of both observer and robust fault-tolerant model predictive controller are obtained by solving the linear matrix inequalities (LMIs). Finally, the efficiency of the proposed RFTPC controller is tested by simulating a numerical example where the simulation results demonstrate the applicability of the proposed method in dealing with linear systems subject to faults in both actuators and sensors.

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