Emotional Fuzzy Sliding-Mode Control for Unknown Nonlinear Systems

[[abstract]]The brain emotional learning model can be implemented with a simple hardware and processor; however, the learning model cannot model the qualitative aspects of human knowledge. To solve this problem, a fuzzy-based emotional learning model (FELM) with structure and parameter learning is proposed. The membership functions and fuzzy rules can be learned through the derived learning scheme. Further, an emotional fuzzy sliding-mode control (EFSMC) system, which does not need the plant model, is proposed for unknown nonlinear systems. The EFSMC system is applied to an inverted pendulum and a chaotic synchronization. The simulation results with the use of EFSMC system demonstrate the feasibility of FELM learning procedure. The main contributions of this paper are (1) the FELM varies its structure dynamically with a simple computation; (2) the parameter learning imitates the role of emotions in mammalians brain; (3) by combining the advantage of nonsingular terminal sliding-mode control, the EFSMC system provides very high precision and finite-time control performance; (4) the system analysis is given in the sense of the gradient descent method.[[notice]]補正完

Variable Structure Feedback Control with Application to Spacecraft with Small Thrust Propulsion Systems

Small spacecrafts requiring small propulsion systems are becoming more popular for low Earth orbit. It is important for these research satellites to have accurate guidance and control systems. Small propulsion systems will also be beneficial for multiple small spacecrafts used future exploration expeditions beyond low Earth orbit. These small spacecrafts benefit from the simplicity of low thrust cold gas propulsion systems. Additionally, large spacecrafts using low thrust, high specific impulse propellants for main propulsion systems, such as ion engines, allow longer and more flexible missions, including Earth orbiting spacecraft and interplanetary spacecraft. In order to extend the life of future planetary exploration missions, it becomes necessary to use In-Situ Resource Utilization (ISRU) to be able to extract resources such as water, oxygen, propellants, and building materials from the local target environment. Small free flying vehicles can be used for quickly surveying planetary surfaces in order to search for potential resource locations. These surveying vehicles can also use such extracted propellants if their propulsion system is designed for it. Cold gas propulsion provides a flexible system to use locally extracted or manufactured propellants. This dissertation investigates nonlinear feedback control techniques for spacecraft with low thrust, cold gas thrust, and spacecraft with cold gas thrust. A model for a cold gas propulsion system is developed for designing control systems for multiple types cold gas thrusters. The model is also used for testing control algorithms in simulation. The cold gas model is validated from a cold gas propulsion hardware testing, and a control law is tested on hardware

A Model-Free Control Algorithm Based on the Sliding Mode Control Method with Applications to Unmanned Aircraft Systems

Control methods require the use of a system model for the design and tuning of the controllers in meeting and/or exceeding the control system performance objectives. However, system models contain errors and uncertainties that also may be complex to develop and to generalize for a large class of systems such as those for unmanned aircraft systems. In particular, the sliding control method is a superior robust nonlinear control approach due to the direct handling of nonlinearities and uncertainties that can be used in tracking problems for unmanned aircraft system. However, the derivation of the sliding mode control law is tedious since a unique and distinct control law needs to be derived for every individual system and cannot be applied to general systems that may encompass all classifications of unmanned aircraft systems. In this work, a model-free control algorithm based on the sliding mode control method is developed and generalized for all classes of unmanned aircraft systems used in robust tracking control applications. The model-free control algorithm is derived with knowledge of the system’s order, state measurements, and control input gain matrix shape and bounds and is not dependent on a mathematical system model. The derived control law is tested using a high-fidelity simulation of a quadrotor-type unmanned aircraft system and the results are compared to a traditional linear controller for tracking performance and power consumption. Realistic type hardware inputs from joysticks and inertial measurement units were simulated for the analysis. Finally, the model-free control algorithm was implemented on a quadrotor-type unmanned aircraft system testbed used in real flight experimental testing. The experimental tracking performance and power consumption was analyzed and compared to a traditional linear-type controller. Results showed that the model-free approach is superior in tracking performance and power consumption compared to traditional linear-type control strategies

Genetic programming for the automatic design of controllers for a surface ship

In this paper, the implementation of genetic programming (GP) to design a contoller structure is assessed. GP is used to evolve control strategies that, given the current and desired state of the propulsion and heading dynamics of a supply ship as inputs, generate the command forces required to maneuver the ship. The controllers created using GP are evaluated through computer simulations and real maneuverability tests in a laboratory water basin facility. The robustness of each controller is analyzed through the simulation of environmental disturbances. In addition, GP runs in the presence of disturbances are carried out so that the different controllers obtained can be compared. The particular vessel used in this paper is a scale model of a supply ship called CyberShip II. The results obtained illustrate the benefits of using GP for the automatic design of propulsion and navigation controllers for surface ships

Analog implementation of a robust control strategy for mechanical systems

An analog implementation of a control structure with disturbance identification for mechanical systems is presented. This control structure is based on a discontinuous observer that estimates the state and the disturbances in the plant, improving the robustness of the closed loop system which also displays a control input free from chattering. The control structure, built with operational amplifiers, is simple, showing good performance for stabilization, regulation, and tracking objectives. The performance of the circuit is compared with a digital implementation based on a real-time data acquisition card to control a simple pendulum. In addition, the circuit performance is illustrated on an industrial 2-DOF robot

Vibration, Control and Stability of Dynamical Systems

From Preface: This is the fourteenth time when the conference “Dynamical Systems: Theory and Applications” gathers a numerous group of outstanding scientists and engineers, who deal with widely understood problems of theoretical and applied dynamics. Organization of the conference would not have been possible without a great effort of the staff of the Department of Automation, Biomechanics and Mechatronics. The patronage over the conference has been taken by the Committee of Mechanics of the Polish Academy of Sciences and Ministry of Science and Higher Education of Poland. It is a great pleasure that our invitation has been accepted by recording in the history of our conference number of people, including good colleagues and friends as well as a large group of researchers and scientists, who decided to participate in the conference for the first time. With proud and satisfaction we welcomed over 180 persons from 31 countries all over the world. They decided to share the results of their research and many years experiences in a discipline of dynamical systems by submitting many very interesting papers. This year, the DSTA Conference Proceedings were split into three volumes entitled “Dynamical Systems” with respective subtitles: Vibration, Control and Stability of Dynamical Systems; Mathematical and Numerical Aspects of Dynamical System Analysis and Engineering Dynamics and Life Sciences. Additionally, there will be also published two volumes of Springer Proceedings in Mathematics and Statistics entitled “Dynamical Systems in Theoretical Perspective” and “Dynamical Systems in Applications”

Sliding Mode Control

The main objective of this monograph is to present a broad range of well worked out, recent application studies as well as theoretical contributions in the field of sliding mode control system analysis and design. The contributions presented here include new theoretical developments as well as successful applications of variable structure controllers primarily in the field of power electronics, electric drives and motion steering systems. They enrich the current state of the art, and motivate and encourage new ideas and solutions in the sliding mode control area

Using a Combination of PID Control and Kalman Filter to Design of IoT-based Telepresence Self-balancing Robots during COVID-19 Pandemic

COVID-19 is a very dangerous respiratory disease that can spread quickly through the air. Doctors, nurses, and medical personnel need protective clothing and are very careful in treating COVID-19 patients to avoid getting infected with the COVID-19 virus. Hence, a medical telepresence robot, which resembles a humanoid robot, is necessary to treat COVID-19 patients. The proposed self-balancing COVID-19 medical telepresence robot is a medical robot that handles COVID-19 patients, which resembles a stand-alone humanoid soccer robot with two wheels that can maneuver freely in hospital hallways. The proposed robot design has some control problems; it requires steady body positioning and is subjected to disturbance. A control method that functions to find the stability value such that the system response can reach the set-point is required to control the robot's stability and repel disturbances; this is known as disturbance rejection control. This study aimed to control the robot using a combination of Proportional-Integral-Derivative (PID) control and a Kalman filter. Mathematical equations were required to obtain a model of the robot's characteristics. The state-space model was derived from the self-balancing robot's mathematical equation. Since a PID control technique was used to keep the robot balanced, this state-space model was converted into a transfer function model. The second Ziegler-Nichols's rule oscillation method was used to tune the PID parameters. The values of the amplifier constants obtained were Kp=31.002, Ki=5.167, and Kd=125.992128. The robot was designed to be able to maintain its balance for more than one hour by using constant tuning, even when an external disturbance is applied to it. Doi: 10.28991/esj-2021-SP1-016 Full Text: PD

Systems Structure and Control

The title of the book System, Structure and Control encompasses broad field of theory and applications of many different control approaches applied on different classes of dynamic systems. Output and state feedback control include among others robust control, optimal control or intelligent control methods such as fuzzy or neural network approach, dynamic systems are e.g. linear or nonlinear with or without time delay, fixed or uncertain, onedimensional or multidimensional. The applications cover all branches of human activities including any kind of industry, economics, biology, social sciences etc