A LOW-COST APPROACH TO DATA-DRIVEN FUZZY CONTROL OF SERVO SYSTEMS

Servo systems become more and more important in control systems applications in various fields as both separate control systems and actuators. Ensuring very good control system performance using few information on the servo system model (viewed as a controlled process) is a challenging task. Starting with authors’ results on data-driven model-free control, fuzzy control and the indirect model-free tuning of fuzzy controllers, this paper suggests a low-cost approach to the data-driven fuzzy control of servo systems. The data-driven fuzzy control approach consists of six steps: (i) open-loop data-driven system identification to produce the process model from input-output data expressed as the system step response, (ii) Proportional-Integral (PI) controller tuning using the Extended Symmetrical Optimum (ESO) method, (iii) PI controller parameters mapping onto parameters of Takagi-Sugeno PI-fuzzy controller in terms of the modal equivalence principle, (iv) closed-loop data-driven system identification, (v) PI controller tuning using the ESO method, (vi) PI controller parameters mapping onto parameters of Takagi-Sugeno PI-fuzzy controller. The steps (iv), (v) and (vi) are optional. The approach is applied to the position control of a nonlinear servo system. The experimental results obtained on laboratory equipment validate the approach

Data-Driven Model-Free Sliding Mode and Fuzzy Control with Experimental Validation

The paper presents the combination of the model-free control technique with two popular nonlinear control techniques, sliding mode control and fuzzy control. Two data-driven model-free sliding mode control structures and one data-driven model-free fuzzy control structure are given. The data-driven model-free sliding mode control structures are built upon a model-free intelligent Proportional-Integral (iPI) control system structure, where an augmented control signal is inserted in the iPI control law to deal with the error dynamics in terms of sliding mode control. The data-driven model-free fuzzy control structure is developed by fuzzifying the PI component of the continuous-time iPI control law. The design approaches of the data-driven model-free control algorithms are offered. The data-driven model-free control algorithms are validated as controllers by real-time experiments conducted on 3D crane system laboratory equipment

A CENTER MANIFOLD THEORY-BASED APPROACH TO THE STABILITY ANALYSIS OF STATE FEEDBACK TAKAGI-SUGENO-KANG FUZZY CONTROL SYSTEMS

The aim of this paper is to propose a stability analysis approach based on the application of the center manifold theory and applied to state feedback Takagi-Sugeno-Kang fuzzy control systems. The approach is built upon a similar approach developed for Mamdani fuzzy controllers. It starts with a linearized mathematical model of the process that is accepted to belong to the family of single input second-order nonlinear systems which are linear with respect to the control signal. In addition, smooth right-hand terms of the state-space equations that model the processes are assumed. The paper includes the validation of the approach by application to stable state feedback Takagi-Sugeno-Kang fuzzy control system for the position control of an electro-hydraulic servo-system

Component-based mixed reality environment for the control and design of servo-pneumatic system

Synopsis Considerable research efforts have been spent over the last two decades on improving the design, control, and modelling of pneumatic servo drive systems including the development of dedicated controllers and control valves. However, the commercial updates in employing pneumatic servos are still largely limited to laboratory research usage and the initiatives in developing seem to have lost their momentums. Although this situation has some to do with the rapid development and availability of cost effective electric servo technologies, one reason is considered to be a lack of design and simulation tools for employing pneumatic servo drives. This research has therefore been conducted to address these concerns, and to demonstrate how appropriate tools and environments can be developed and used to aid in the design, control and commissioning of pneumatic servo drives. Because of the inherent high nonlinearities associated with pneumatic systems, it would be highly desirable if the simulation environment could be run in time domain so that it can be mixed with the real system. This would make the simulation more accurate and reliable especially when dealing with such nonlinear systems. Unfortunately, the tools that are available in the market such as Propneu (Festo, 2005) and Hypneu (Bardyne, 2006) are dedicated for pneumatic circuit design only. This research is aimed at developing a mixed reality environment for the control and design of servo-pneumatic systems. Working with a mixed reality environment would include both the capability to model the system entirely as a simulation, the so-called "off-line", as well as being able to use real components running against simulations of others "on-line", or in a Mixed Reality (MR) manner. Component-based paradigm has been adopted, and hence the entire pneumatic system is viewed as a series of component modules with standardised linking variables. The mathematical model of each individual component has been implemented in simulation software which produces time domain responses in order to allow for mixing the simulation with the real system. The main outcome of this research can be seen as a successful development and demonstration of the Component-based Mixed Reality Environment (CMRE), which would facilitate the control and design of servo-pneumatic systems. On the one hand, the CMRE facilitates the identification of some nonlinear parameters such as frictional \I ynopsis parameters. These parameters could cause great difficulties in servo-pneumatic modelling and control. Accurate friction parameters would give the ability to attain an accurate model, and therefore provide more flexibility in applying different control and tuning strategies on the real system. On the other hand, the CMRE facilitates the design process by enabling the designer to evaluate the servo-pneumatic system off-line prior to building the system. This would reduce the design time, increase the reliability of the design, and minimize the design cost. The concept of the CMRE was validated by tests carried out on laboratory-based prototype servo-drive. Close agreement between the experimental and simulated responses was obtained showing that the models have represented the real system adequately. Case studies were then conducted to demonstrate the validity of the proposed methodology and environment. In these case studies, PIDVF controller and cascade control structure were successfully implemented, synthesised, and tuned. The results revealed that the CMRE is an easy, accurate and robust way of implementing different control and tuning strategies on servo-pneumatic systems. Furthermore, the research has shown how the CMRE can lead to significant improvements in certain life cycle phases of the system, e.g. commissioning, maintenance, etc. This research has contributed to knowledge in the following: (1) Adopting the mixed reality concept and the component-based approach in order to create a CMRE in facilitating the control and design of servo-pneumatic systems. (2) A method to identify the friction parameters of a single-axis pneumatic machine, (3) Encapsulate existing control methods within the CMRE to be applied on the real system. (4) A scheme for controller tuning, in which the controller is tuned off-line and then applied on the real system, and hence avoided on-line tuning which can be troublesome and time consuming. It is anticipated that the concept of the CMRE can be extended to include multi-axes servo-pneumatic system, servo-hydraulic, and servo-electric drives. Therefore, conceptual model structures have been introduced in this research which can be considered as the foundation for creating similar environments for those systems

Influence of feed drives on the structural dynamics of large-scale machine tools

Milling is one of the most widely used processes in the manufacturing industry and demands machines with high productivity rates. In large machine tool applications, the cutting capability is mainly limited by the appearance of structural chatter vibrations. Chatter arises from the dynamic interaction of the machining system compliance with the cutting process. For the specific case of large-scale machine tools, the low frequency resonances have modal shapes that generate relative displacements in the machine joints. This thesis presents new approaches to minimize the appearance of chatter vibrations by targeting and understanding the machine tool compliance, in particular, from the feed drive of the machine tool. A detailed model of the double pinion and rack feed drive system and the master-slave coupling improves the large machine tools modeling. As the vibrations are measured by the axes feedback sensors, a new strategy for feed drive controller tuning allows increasing the chatter stability using a judicious selection of the servo parameters. Then, in-motion dynamic characterizations demonstrate the important influence of the nonlinear friction on the machine compliance and improve the chatter stability predictions. Finally, an operational method for characterizing both tool and workpiece side dynamics while performing a cutting operation is developed. All the contributions of the thesis have been validated experimentally and tend to consider the influence of the feed drives on the structural dynamics of large-scale machine tools

Iterative learning control in the commissioning of industrial presses

182 p.This thesis presents solutions to the control problems that exist nowadays in industrial presses, followed by a discussion of the most appropriate control schemes that may be used for their solution. Iterative Learning Control is subsequently analyzed, as the most promising control scheme for machine presses, due to its capability to improve the performance of a system that operates repeatedly.A novel Iterative Learning Control design is presented, which makes use of the dynamic characteristics of the system to improve the current controller performance and stability. This, results in an adaptation of the presented Iterative Learning Control design to two use cases: the single-input-single-output force control of mechanical presses and the multiple-input-multiple-output position control of hydraulic presses. While existing Iterative Learning Control approaches are also described and applied to the previously mentioned use cases, the presented novel approach has been shown to outperform the existing algorithms in terms of control performance.The proposed Iterative Learning control algorithms are validated in an experimental hydraulic test rig, in which the performance, robustness and stability of the algorithm have been demonstrated

Design, Development, and Testing of Near-Optimal Satellite Attitude Control Strategies

Advances in space technology and interest toward remote sensing mission have grown in the recent years, requiring the attitude control subsystems of observation satellites to increase their performances in terms of pointing accuracy and on-board implementability. Moreover, an increased interest in small satellite missions and the recent technological developments related to the CubeSats standard have drastically reduced the cost of producing and flying a satellite mission. In this context, the proposed research aims to improve the state of the art for satellite attitude control methodologies by proposing a near-optimal attitude control strategy, simulated in a high-fidelity environment. Two strategies are presented, both are based on the implementation of a direct method, the Inverse Dynamics in the Virtual Domain (IDVD), and a nonlinear programming solver, the Sequential Gradient-Restoration Algorithm (SGRA). The IDVD allows the transcription of the original optimal control problem into an equivalent nonlinear programming problem. SGRA is adopted for the quick determination of near-optimal attitude trajectories. The two optimization criteria considered are the target acquisition time and the maneuver energy associated to the actuation torques. In addition, the development and initial testing of a satellite attitude simulator testbed for on-ground experimentation of attitude, determination, and control methodologies is proposed. The Suspended Satellite Three-Axis Rotation Testbed (START) is a novel low-cost satellite three-axis attitude simulator testbed, it is located at the Aerospace Robotics Testbed Laboratory (ARTLAB). START is mainly composed by a 3D printed base, a single-board computer, a set of actuators, and an electric battery. The suspension system is based on three thin high tensile strength wires allowing a three degrees-of freedom rotation range comparable to the one of air bearing-based floating testbeds, and minimal resistive torque in all the rotations axis. This set up will enable the hardware in-the-loop experimentation of attitude guidance navigation and control strategies. Finally, a set of guidelines to select a solver for the solution of nonlinear programming problems is proposed. With this in mind, a comparison of the convergence performances of commonly used solvers for both unconstrained and constrained nonlinear programming problems is presented. The terms of comparison involve accuracy, convergence rate, and convergence speed. Because of its popularity among research teams in academia and industry, MATLAB is used as common implementation platform for the solvers

Teaching Motion Control in Mechatronics Education Using an Open Framework Based on the Elevator Model

Universities and other educational institutions may find it difficult to afford the cost of obtaining cutting-edge teaching resources. This study introduces the adoption of a novel open prototyping framework in the context of mechatronics education, employing low-cost commercial off-the-shelf (COTS) components and tools for the motion control module. The goal of this study is to propose a novel structure for the motion control module in the engineering mechatronics curriculum. The objective is to foster a new teaching method. From a methodology perspective, students are involved in a series of well-organised theoretical lectures as well as practical, very engaging group projects in the lab. To help students understand, draw connections, and broaden their knowledge, the methods of surface learning and deep learning are frequently mixed thoroughly. The structure of the course as well as the key topics are discussed. The proposed open framework, which consists of an elevator model, is presented in details. Students’ early evaluation indicates that the course organisation and subjects are successful and beneficial.publishedVersio

Control and Automation

Control and automation systems are at the heart of our every day lives. This book is a collection of novel ideas and findings in these fields, published as part of the Special Issue on Control and Automation. The core focus of this issue was original ideas and potential contributions for both theory and practice. It received a total number of 21 submissions, out of which 7 were accepted. These published manuscripts tackle some novel approaches in control, including fractional order control systems, with applications in robotics, biomedical engineering, electrical engineering, vibratory systems, and wastewater treatment plants. This Special Issue has gathered a selection of novel research results regarding control systems in several distinct research areas. We hope that these papers will evoke new ideas, concepts, and further developments in the field