Failure diagnosis and tolerant control method for hydrothermally aged SCR system by utilizing EKF observer and MRAC controller

This paper studies the practical use of discrete-time direct adaptive control in a high-precision inertially stabilized platform's turbulence isolation system for the purpose of enhancing isolation performance. Under low-frequency and low-velocity environments, the velocity-stabilized loop of the platform shows severe nonlinear characteristic; therefore, its isolation performance is limited. In previous research, we constructed a nonlinear model of the velocity-stabilized loop by using an improved Stribeck friction model, and also designed a feed-forward compensation strategy. Both have obtained outstanding performance during practical experiments. However, errors still exist as disturbance of the unmodeled part and environmental change causes the system's parameter to vary. To solve this, a novel discrete-time direct model reference adaptive control based on nonlinear friction compensation is introduced to the original proportional-integral control system. An improved projection algorithm and a recursive least-square algorithm with fading memory are respectively used to design the adaptive law. By using a turbulence observer to provide a reference signal, both types of controls are applied to the carrier turbulence isolation system. Results of the practical experiments prove that model reference adaptive control can further enhance the system's isolation ability.

Discrete-Time Direct Model Reference Adaptive Control Application in a High-Precision Inertially Stabilized Platform

Magnetic Levitation is a process in which an object is suspended with the support of the magnetic field. Despite being an unstable system, Magnetic Levitation Systems (MAGLEV) have profound applications in various fields of engineering. MAGLEV systems are sensitive, unstable, and nonlinear and uncertainties always pose a challenge in Controller Design. As a solution, adaptive controllers came into existence with adaptation mechanisms to cover the system uncertainties. In this study, a simple, novel, and an effective approach to the Enhanced Adaptive Control scheme is proposed for the ball position control and tracking of an unstable Magnetic Levitation System. The proposed Enhanced Model Reference Adaptive Scheme (EMRAC) follows the same phenomenon of the Model Reference Adaptive Scheme (MRAC) with a slight difference in its control strategy. The proposed scheme consists of Proportional-Integral-Velocity plus Feed Forward as the control structure and a modified version of the standard tuning rule is used as the adaptation mechanism. The control scheme is applied to a standard benchmark Magnetic Levitation System and the tracking performance of the scheme is tested by applying square and multi-sine pattern trajectories to the Magnetic Levitation System. The performance of the developed Enhanced MRAC performance is compared with that of the Proportional Integral Velocity with Feedforward Control (PIV+FF) scheme and the proposed control scheme is proven to be more suitable. The performance of the proposed scheme is also analyzed with Power Spectral Density and Root Mean Square Error to evaluate the ball position tracking control. It is inferred from the experimental results that Enhanced MRAC accommodates the changes and makes the system more reliable with good tracking ability.

Enhanced Model Reference Adaptive Control Scheme for Tracking Control of Magnetic Levitation System

This paper presents a comparison of two different adaptive control schemes for improving the performance of a hybrid wind-diesel power system in an islanded microgrid configuration against the baseline controller, IEEE type 1 automatic voltage regulator (AVR). The first scheme uses a model reference adaptive controller (MRAC) with a proportional-integral-derivative (PID) controller tuned by a genetic algorithm (GA) to control the speed of the diesel engine (DE) for regulating the frequency of the power system and uses a classical MRAC for controlling the voltage amplitude of the synchronous machine (SM). The second scheme uses a MRAC with a PID controller tuned by a GA to control the speed of the DE, and a MRAC with an artificial neural network (ANN) and a PID controller tuned by a GA for controlling the voltage amplitude of the SM. Different operating conditions of the microgrid and fault scenarios in the diesel engine generator (DEG) were tested: 1) decrease in the performance of the diesel engine actuator (40% and 80%), 2) sudden connection of 0.5 MW load, and 3) a 3-phase fault with duration of 0.5 seconds. Dynamic models of the microgrid components are presented in detail and the proposed microgrid and its fault-tolerant control (FTC) are implemented and tested in the Simpower Systems of MATLAB/Simulink® simulation environment. The simulation results showed that the use of ANNs in combination with model-based adaptive controllers improves the FTC system performance in comparison with the baseline controller.

Model-based fault-tolerant control to guarantee the performance of a hybrid wind-diesel power system in a microgrid configuration

This work proposes a fully nonlinear model for a pneumatic process control valve. Since it reproduces stiction and hysteresis, it can be used as a tool for developing accurate control schemes for the whole process and/or facilitate the tuning of control parameters in "smart" process control valves. The performance of the model is evaluated experimentally.

Nonlinear Dynamic Modeling of a Pneumatic Process Control Valve

In this paper, a modified version of Variable Structure Model Reference Adaptive Controller (VS-MRAC) scheme is developed for an application in Fault Tolerant Control (FTC) of a Single Input-Single Output (SISO) process. As a result of steady state error and oscillations when faults are induced in sensor and actuator of the process, the original VS-MRAC is modified by adding a Saturation Function and a PI controller (VS-MRAC-SAT-PI). The new scheme performance is compared against a classical PID and two other MRAC-based FTC schemes in a Coupled-Tank System. Different types of additive faults (abrupt and gradual faults) were induced in the process and results showed better fault accommodation capabilities of the VS-MRAC-SAT-PI.

MRAC-based Fault Tolerant Control of a SISO Real Process Application

It is widely recognized that a hands-on laboratory experience is useful in control engineering education. Herein, the students overcome the main gaps between theoretical knowledge and experimental setups. Nowadays, in times of crisis due to the COVID-19 pandemic, virtual and remote laboratories are emerging as primary educational resources. However, in virtual labs, the students are not exposed to real life issues (i.e., equipment problems, noise, etc.) while in remote labs, communication and connectivity problems arise (i.e., network security, synchronization management, internet speed, etc.). Henceforth, this work presents an unpublished educational project named Lab-Tec@Home, and the aim of this research is to expand the access of hands-on control education at the undergraduate level. Here, students easily assemble a cost-effective laboratory kit at home and use it on their own computing devices connected with the external MATLAB/SimulinkTM application. Thus, students can test and validate theoretical concepts of control engineering such as: system model identification, and PID control design and test. The assessment results show that the proposed educational project enhances the learning experience and has outstanding positive feedback of more than 290 students who undertook massive flexible digital courses at Tecnologico de Monterrey. This makes the proposed educational project mainly suitable for control engineering courses.

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Lab-Tec@Home: A Cost-Effective Kit for Online Control Engineering Education

Artificial Intelligence Methods in Fault Tolerant Control

This paper presents two model-based approaches for designing control strategies in order to integrate a diesel generator as frequency and voltage leader in an islanded microgrid configuration. The selected microgrid configuration is composed of a hybrid wind-diesel system with a battery storage system (BSS). A model predictive control (MPC) scheme and a model reference adaptive control (MRAC) scheme are selected for this task, due to its flexibility and capability for handling constraints and fault-tolerance, respectively, which is helpful for smart grid (SG) architectures to achieve reduced fuel consumption and with and enhanced reliability and integration of renewable energy sources (RES) into the electrical network. A constrained fuel consumption strategy has been implemented in the diesel engine generator (DEG) controller with the help of MPC strategy and fault-tolerance is achieved with MRAC. Different operating conditions of the microgrid were simulated: 1) diesel-only generation, 2) wind turbine generator (WTG) ignition, 3) sudden connection of 0.5 MW load, and 4) a 3-phase fault with duration of 0.5 seconds. Improved performance over a baseline controller, IEEE type 1 automatic voltage regulator (AVR), is achieved. Dynamic models of the network components are presented in details on design and implementation of the microgrid configuration in Matlab/Simulink R .

Model-based Control Approaches for Optimal Integration of a Hybrid Wind-diesel Power System in a Microgrid

The performance of biomimetic underwater vehicles directly depends on the correct design of their propulsion system and its control. These vehicles can attain highly efficient motion, hovering and thrust by properly moving part(s) of their bodies. In this article, a mathematical modeling and waypoint guidance system for a biomimetic autonomous underwater vehicle (BAUV) is proposed. The BAUV achieves sideways and dorsoventral thunniform motion by flapping its caudal fin through a parallel mechanism. Also, an analysis of the vehicle’s design is presented. A thrust analysis was performed based on the novel propulsion system. Furthermore, the vehicle’s kinematics and dynamic models were derived, where hydrodynamic equations were obtained as well. Computed models were validated using simulations where thrust and moment analysis was employed to visualize the vehicle’s performance while swimming. For the path tracking scheme, a waypoint guidance system was designed to correct the vehicle’s direction toward several positions in space. To accurately obtain waypoints, correction over the propeller’s flapping frequency and bias was employed to achieve proper thrust and orientation of the vehicle. The results from numerical simulations showed how by incorporating this novel propulsion strategy, the BAUV improved its performance when diving and maneuvering based on the dorsoventral and/or sideways configuration of its swimming mode. Furthermore, by designing proper strategies to regulate the flapping performance of its caudal fin, the BAUV followed the desired trajectories. The efficiency for the designed strategy was obtained by comparing the vehicle’s traveled distance and ideal scenarios of straight-line trajectories between targets. During simulations, the designed guidance system presented an efficiency of above 80% for navigation tasks.

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Modeling, Trajectory Analysis and Waypoint Guidance System of a Biomimetic Underwater Vehicle Based on the Flapping Performance of Its Propulsion System

Adriana Vargas Martinez

Papers

MRAC-based Fault Tolerant Control of a SISO Real Process Application

Lab-Tec@Home: A Cost-Effective Kit for Online Control Engineering Education

Artificial Intelligence Methods in Fault Tolerant Control

Model-based Control Approaches for Optimal Integration of a Hybrid Wind-diesel Power System in a Microgrid

Modeling, Trajectory Analysis and Waypoint Guidance System of a Biomimetic Underwater Vehicle Based on the Flapping Performance of Its Propulsion System