Robot visual servoing with iterative learning control.

YesThis paper presents an iterative learning scheme for vision guided robot trajectory tracking. At first, a stability criterion for designing iterative learning controller is proposed. It can be used for a system with initial resetting error. By using the criterion, one can convert the design problem into finding a positive definite discrete matrix kernel and a more general form of learning control can be obtained. Then, a three-dimensional (3-D) trajectory tracking system with a single static camera to realize robot movement imitation is presented based on this criterion

Design and development of the ‘POD Adventures’ smartphone game: a blended problem-solving intervention for adolescent mental health in India

Introduction: Digital technology platforms offer unparalleled opportunities to reach vulnerable adolescents at scale and overcome many barriers that exist around conventional service provision. This paper describes the design and development of POD Adventures, a blended problem-solving game-based intervention for adolescents with or at risk of anxiety, depression and conduct difficulties in India. This intervention was developed as part of the PRemIum for ADolEscents (PRIDE) research programme, which aims to establish a suite of transdiagnostic psychological interventions organised around a stepped care system in Indian secondary schools. Methods and materials: Intervention development followed a person-centered approach consisting of four iterative activities: (i) review of recent context-specific evidence on mental health needs and preferences for the target population of school-going Indian adolescents, including a multiple stakeholder analysis of school counselling priorities and pilot studies of a brief problem-solving intervention; (ii) new focus group discussions with N=46 student participants and N=8 service providers; (iii) co-design workshops with N=22 student participants and N=8 service providers; and (iv) user-testing with N=50 student participants. Participants were aged 12-17 years and recruited from local schools in New Delhi and Goa, including a subgroup with self-identified mental health needs (N=6). Results: Formative data from existing primary sources, new focus groups and co-design workshops supported a blended format for delivering a brief problem-solving intervention, with counsellors supporting use of a game-based app on ‘offline’ smartphones. User-testing with prototypes identified a need for simplification of language, use of concrete examples of concepts and practice elements to enhance engagement. There were also indications that participants most valued relatability and interactivity within real-world stories with judicious support from an in-app guide. The final prototype comprised a set of interactive and gamified vignettes and a structured set of problem-solving questions to consolidate and generalise learning while encouraging real-world application. Discussion: Findings shaped the design of POD Adventures and its delivery as an open-access blended intervention for secondary school students with a felt need for psychological support, consistent with an early intervention paradigm. A randomised controlled trial is planned to evaluate processes and impacts of POD Adventures when delivered for help-seeking students in low-resource school settings

Application d’un algorithme de contrôle par apprentissage itératif à un four de thermoformage

Le thermoformage est un procédé industriel qui consiste à chauffer une feuille de plastique jusqu’à ce que celle-ci soit ductile pour ensuite la mouler à sa forme finale. Actuellement en industrie, les consignes des éléments chauffants des fours sont ajustées par un opérateur. Celui-ci doit constamment ajuster les commandes pour palier aux différentes perturbations affligeant le système. Une erreur de sa part engendre des pièces de mauvaise qualité, ce qui amène une baisse de la productivité et une hausse des coûts. Dans ce mémoire nous tenterons d’appliquer une technique de contrôle dite par apprentissage itératif pour faire le contrôle en temps réel d’un four de thermoformage radiant. Cette stratégie de contrôle est simple et réagit bien aux différentes perturbations induites dans le système

Iterative learning control for robot manipulators

When a system is performing the same task repeatedly it is, from an engineering perspective, advantageous to use the knowledge from the previous iterations of the same task in order to reduce the error on successive trials. In control systems, the aim is to force the system output to follow a desired trajectory as closely as possible. Specific norms and measures of optimality are used to determine how close the output is to the desired trajectory. Although control theory provides many different possible solutions for such problem, it is not always possible to achieve a desired set of performance requirements. This may be due to the presence of unmodeled dynamics or parametric uncertainties exhibited during the system operation, or due to the lack of suitable design techniques for particular class of systems. Iterative learning control (ILC) is a relatively new addition to these techniques that, for a particular class of problems, can be used to overcome some of the difficulties associated with performance design of control systems

Implementation of Iterative Learning Control on a Pneumatic Actuator.

Masters Degree. University of KwaZulu-Natal, Durban.Pneumatic systems play a pivotal role in many industrial applications, such as in petrochemical industries, steel manufacturing, car manufacturing and food industries. Besides industrial applications, pneumatic systems have also been used in many robotic systems. Nevertheless, a pneumatic system contains different nonlinear and uncertain behaviour due to gas compression, gas leakage, attenuation of the air in pipes and frictional forces in mechanical parts, which increase the system’s dynamic orders. Therefore, modelling a pneumatic system tends to be complicated and challenges the design of the controller for such a system. As a result, employing an effective control mechanism to precisely control a pneumatic system for achieving the required performance is essential. A desirable controller for a pneumatic system should be capable of learning the dynamics of the system and adjusting the control signal accordingly. In this study, a learning control scheme to overcome the highlighted nonlinearity problems is suggested. Many industrial processes are repetitive, and it is reasonable to make use of previously acquired data to improve a controller’s convergence and robustness. An Iterative Learning Control (ILC) algorithm uses information from previous repetitions to learn about the system’s dynamics. The ILC algorithm characteristics are beneficial in real-time control given its short time requirements for responding to input changes. Cylinder-piston actuators are the most common pneumatic systems, which translate the air pressure force into a linear mechanical motion. In industrial automation and robotics, linear pneumatic actuators have a wide range of applications, from load positioning to pneumatic muscles in robots. Therefore, the aim of this research is to study the performance of ILC techniques in position control of the rod in a pneumatic position-cylinder system. Based on theoretical analysis, the design of an ILC is discussed, showing that the controller can satisfactorily overcome nonlinearities and uncertainties in the system without needing any prior knowledge of the system’s model. The controller has been designed in such a way to even work on non-iterative processes. The performance of the ILC-controlled system is compared with a well-tuned PID controller, showing a faster and more accurate response

Hybrid intelligent machine systems : design, modeling and control

To further improve performances of machine systems, mechatronics offers some opportunities. Traditionally, mechatronics deals with how to integrate mechanics and electronics without a systematic approach. This thesis generalizes the concept of mechatronics into a new concept called hybrid intelligent machine system. A hybrid intelligent machine system is a system where two or more elements combine to play at least one of the roles such as sensor, actuator, or control mechanism, and contribute to the system behaviour. The common feature with the hybrid intelligent machine system is thus the presence of two or more entities responsible for the system behaviour with each having its different strength complementary to the others. The hybrid intelligent machine system is further viewed from the system’s structure, behaviour, function, and principle, which has led to the distinction of (1) the hybrid actuation system, (2) the hybrid motion system (mechanism), and (3) the hybrid control system. This thesis describes a comprehensive study on three hybrid intelligent machine systems. In the case of the hybrid actuation system, the study has developed a control method for the “true” hybrid actuation configuration in which the constant velocity motor is not “mimicked” by the servomotor which is treated in literature. In the case of the hybrid motion system, the study has resulted in a novel mechanism structure based on the compliant mechanism which allows the micro- and macro-motions to be integrated within a common framework. It should be noted that the existing designs in literature all take a serial structure for micro- and macro-motions. In the case of hybrid control system, a novel family of control laws is developed, which is primarily based on the iterative learning of the previous driving torque (as a feedforward part) and various feedback control laws. This new family of control laws is rooted in the computer-torque-control (CTC) law with an off-line learned torque in replacement of an analytically formulated torque in the forward part of the CTC law. This thesis also presents the verification of these novel developments by both simulation and experiments. Simulation studies are presented for the hybrid actuation system and the hybrid motion system while experimental studies are carried out for the hybrid control system

Experimental evaluation of some classical and adaptive iterative learning control schemes on a 5DOF robot manipulator

In many process industries (e.g., VLSI production lines, Automotive industries, IC welding process, inspections, manipulations), robot manipulators are used to perform the same tasks repeatedly over a finite time interval. The ultimate goal of robotic research is to design intelligent and autonomous robot control systems to perform repetitive tasks that are dull, hazardous, or require skill beyond the capability of humans. The nonlinear nature of the robot dynamics has made this problem a challenging one in robotics research. This highly demanding control problem of driving an industrial robot to follow a desired trajectory perfectly under constrained or unconstrained environment has led to the application of sophisticated control techniques. From the classical or modern control view point, it is a very difficult task to design an intelligent robot control system that can achieve perfect tracking over a finite time interval due to the effect of highly coupled robot dynamics and the presence of the unmodeled dynamics such as friction and backlash that are usually exhibited in the robot system during actual operation

Next generation automotive embedded systems-on-chip and their applications

It is a well known fact in the automotive industry that critical and costly delays in the development cycle of powertrain1 controllers are unavoidable due to the complex nature of the systems-on-chip used in them. The primary goal of this portfolio is to show the development of new methodologies for the fast and efficient implementation of next generation powertrain applications and the associated automotive qualified systems-on-chip. A general guideline for rapid automotive applications development, promoting the integration of state-of-the-art tools and techniques necessary, is presented. The methods developed in this portfolio demonstrate a new and better approach to co-design of automotive systems that also raises the level of design abstraction.An integrated business plan for the development of a camless engine controller platform is presented. The plan provides details for the marketing plan, management and financial data.A comprehensive real-time system level development methodology for the implementation of an electromagnetic actuator based camless internal combustion engine is developed. The proposed development platform enables developers to complete complex software and hardware development before moving to silicon, significantly shortening the development cycle and improving confidence in the design.A novel high performance internal combustion engine knock processing strategy using the next generation automotive system-on-chip, particularly highlighting the capabilities of the first-of-its-kind single-instruction-multiple-data micro-architecture is presented. A patent application has been filed for the methodology and the details of the invention are also presented.Enhancements required for the performance optimisation of several resource properties such as memory accesses, energy consumption and execution time of embedded powertrain applications running on the developed system-on-chip and its next generation of devices is proposed. The approach used allows the replacement of various software segments by hardware units to speed up processing.1 Powertrain: A name applied to the group of components used to transmit engine power to the driving wheels. It can consist of engine, clutch, transmission, universal joints, drive shaft, differential gear, and axle shafts

An iterative learning controller with initial state learning

10.1109/9.746269IEEE Transactions on Automatic Control442371-376IETA