Control Engineering Engineers, Part I: Journal of ...

Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering http://pii.sagepub.com/

Guest Editorial Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering 2011 225: 705 DOI: 10.1177/0959651811418487 The online version of this article can be found at: http://pii.sagepub.com/content/225/6/705

Published by: http://www.sagepublications.com

On behalf of:

Institution of Mechanical Engineers

Additional services and information for Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering can be found at: Email Alerts: http://pii.sagepub.com/cgi/alerts Subscriptions: http://pii.sagepub.com/subscriptions Reprints: http://www.sagepub.com/journalsReprints.nav Permissions: http://www.sagepub.com/journalsPermissions.nav Citations: http://pii.sagepub.com/content/225/6/705.refs.html

Downloaded from pii.sagepub.com at STAFFORDSHIRE UNIV on September 13, 2011

705

Guest Editorial DOI: 10.1177/0959651811418487

SPECIAL ISSUE ON HUMAN ADAPTIVE MECHATRONICS Mechatronics is a synergetic integration of diverse technologies driven by the needs of humans and industry. It includes mechanical, electrical, information technology, systems, and control engineering. To improve the performance of a mechatronic system, it should adapt to the level of skill or dexterity of its users or operators, and should assist them to improve their skills. To achieve this, the adaptive mechatronic systems, including the human in the loop, should be studied. Thus a new discipline of the synergetic integration of mechatronics with human sciences, such as medical science and psychology, named ‘Human Adaptive Mechatronics (HAM)’ [1–3], has been created. HAM is an intelligent electrical–mechanical system that is able to adapt itself to the human’s skill in various environments and provide assistance in improving the skill and overall operation of the combined human–machine system to achieve better performance. The HAM concept was first proposed in the COE project (2003–2008) at Tokyo Denki University [1, 2]. The EPSRC UK–Japan HAM network was active between March 2007 and September 2010, and its members have successfully initiated research on HAM [3] (www.EPSRCHAMNetwork.org.uk). The research performed by the network members covers intelligent and advanced control, advanced mechatronics and robotics, and human–machine systems with applications. The guest editors had originally planned to solicit papers selected from those presented at the HAM workshop run by the EPSRC UK–Japan HAM network, at Loughborough University, UK, in May 2010, but to promote HAM study worldwide it was extended to invite papers from the international community. This issue, published in Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering, consists of 14 papers that are categorized into the following five areas. 1. DEMONSTRATION OF THE HAM CONCEPT Assisting control for pendulum-like juggling in human adaptive mechatronics, by K. Furuta et al., whose team first proposed the HAM concept in 2003, presents a human adaptive assisting system to support the user’s learning by involving performance retention against user’s disoperation as an example to demonstrate the system design from the HAM view. The paper proposes a HAM-like control structure in a human– machine interface operation, investigating its effectiveness and control characteristics of the trained operators using a force-feedback haptic interface device with the pendulum-like juggling task. 2. HUMAN–MACHINE SYSTEMS Human performance index – a generic performance indicator, by T. Parthornratt et al., investigates human skill evaluation and human skill quantification from the HAM view. The paper proposes a HPI concept to focus on human performance by considering the quantification of speed–accuracy characteristics, based on Fitts’ classical speed–accuracy trade-off, and determination of human control strategy involved in completing a task. The experiment results in a computer-based, simple tracking system by using a computer mouse to follow a set of random circles on a display to Ó SAGE Publications Ltd 2011

Proc. IMechE Vol. 225 Part I: J. Systems and Control Engineering Downloaded from pii.sagepub.com at STAFFORDSHIRE UNIV on September 13, 2011

706

demonstrate how the HPI concept can be applied, which strongly relies on the fact that a suitable speed and accuracy ratio is obtainable. Measurement of attention and emotion levels for human adaptive mechatronics by near infrared spectroscopy, by K. Furuta et al., presents a method to measure the attention and emotion levels using the near infrared spectroscopy (NIRS) signals around the prefrontal cortex. The paper proposes a hypothesis that the emotion of happiness and sadness and attention levels are related to the power and its distribution function of the first principal components of the measured signals by the NIRS around the brain cortex. To verify the hypothesis, the analysis has been carried out through experiments in which normal and dementia subjects watch videos. From the experiment, the data of dementia subjects show that the attention and emotion are irrelevant, contrary to those of normal subjects. 3. INTELLIGENT AND ADVANCED CONTROL 3.1 Control theory and methods Accelerated predictive norm-optimal iterative learning control, by B. Chu and D. H. Owens, investigates iterative learning control (ILC) required by many HAM systems. The paper proposes a novel technique for accelerating the predictive norm-optimal iterative learning control (NOILC) methodology that leads to two proposed accelerated algorithms together with well-defined convergence properties. The results show that the proposed accelerated algorithms are capable of ensuring monotonic error norm reductions and can outperform predictive NOILC by more rapid reductions in error norm from iteration to iteration. Isomorphism-based robust right coprime factorization realization for non-linear feedback systems, by N. Bu and M. Deng, considers the realization of system design problems for non-linear feedback control systems using the robust right coprime factorization and isomorphism. The paper proposes a sufficient condition that guarantees the stability of the constructed isomorphic subspace of input space and develops a quantitative design scheme to guarantee the robust stability of the non-linear feedback system and the plant output tracking to the reference input. A bio-inspired controller for unmanned aerial vehicles in chemical cloud coverage, by J. Oyekan et al., investigates the bio-inspired control issues using bacteria chemotaxis behaviour and flocking behaviour from nature. The paper proposes a bio-inspired controller that is capable of controlling a swarm of unmanned aerial vehicles to provide a visual representation of an invisible airborne hazardous substance, such as a chemical cloud. An optimal regulator for stabilization of multi-joint reaching movements under DOF redundancy: a challenge to the Bernstein problem from a control-theoretic viewpoint, by S. Arimoto and M. Sekimoto, investigates an optimal regulator problem for multi-joint reaching movements of redundant manipulators. The paper shows that, in the case of infinite time horizon [t0, N), the optimal control reduces to a task–space velocity feedback and the Hamilton–Jacobi equation becomes solvable in an explicit quadratic form. It also presents a functional relationship of the optimal regulator with the passivity of the closed-loop dynamics. 3.2 Control applications Adaptive neural network tracking control of robot manipulators with prescribed performance, by X.-L. Xie et al., investigates the control issues of robot manipulators using neural networks. The paper proposes a control approach for robot manipulators that can guarantee the tracking error of the systems bounded by predefined decreasing boundary. Control of flexible joint robot manipulators using a combined controller with neural network and linear regulator, by Z.-H. Jiang and S. Higaki, studies the issue of dynamic trajectory tracking control of flexible joint robot manipulators. The paper proposes Proc. IMechE Vol. 225 Part I: J. Systems and Control Engineering Downloaded from pii.sagepub.com at STAFFORDSHIRE UNIV on September 13, 2011

Ó SAGE Publications Ltd 2011

707

a new control strategy using the combination of a linear feedback law and a neural network mapping. Actuator fault detection on a process control experimental system using combined observers, by M. Deng et al., investigates the fault detection issues of a process control system. The paper proposes an unknown parameter identification mechanism by combining with the disturbance observer to deal with the fault detection problem with uncertainties. 4. ADVANCED MECHATRONICS AND ROBOTICS Slip parameter estimation for tele-operated ground vehicles in slippery terrain, by X. Song et al., studies the issues on operating a ground vehicle remotely, which requires a cooperative activity between the vehicle and the operator. The paper proposes a slip estimation approach using an optical flow technique and a non-linear observer. The proposed approach is evaluated on test rigs and a skid-steering mobile robot. Design of HyQ – a hydraulically and electrically actuated quadruped robot, by C. Semini et al., focuses on the development of a mobile robotic platform. The paper builds a new versatile hydraulically-powered quadruped robot (HyQ) to serve as a platform to study, not only highly dynamic motions such as running and jumping, but also careful navigation over very rough terrain. It describes design and specifications of the robot and presents details on the hardware of the quadruped platform, such as the mechanical design of the four articulated legs and of the torso frame, and the configuration of the hydraulic power system. 5. HAM APPLICATIONS Phase-lead iterative learning control algorithms for functional electrical stimulationbased stroke rehabilitation, by C. T. Freeman et al. considers the stroke rehabilitation issues using the control and robotic technology. The paper develops a control system for stroke rehabilitation that combines electrical stimulation with a robotic support system to provide assistance to stroke patients performing three-dimensional upper limb reaching tasks in a virtual reality environment. The electrical stimulation is applied to two muscles in the subject’s arm using the iterative learning control schemes in order to achieve highly accurate movement. Design, kinematics, simulation, and experiment for a lower-limb rehabilitation robot, by H. Wang et al., investigates design and development of intelligent rehabilitation robots. The paper proposes a lower limb rehabilitation robot that is used to help people who suffer paralysis caused by disease or lower limb movement disorder following an accident to improve and resume limb functions. The developed rehabilitation robot has a novel feature where three rotary joints consist of three crank rocker mechanisms with an identical module. The paper covers mechanism design and optimization, kinematics analysis and trajectory planning, motion simulation, the control system design, and experiments. We would like to thank all authors for their contributions, and all the reviewers for their helpful and constructive comments. We would also like to thank the Editor-inChief of the Proceedings of the Institution of Mechanical Engineers, Journal of Systems and Control Engineering, the Managing Editor, Ms L. Strain, and Assistant Managing Editor, Ms H. Elmes for their support and guidance in organizing this special issue. REFERENCES 1 Furuta, K. Control of Pendulum: From Super Mechano-system to Human Adaptive Mechatronics. In Proceedings of the 42nd IEEE Conference on Decision and control, Maui, Hawaii, USA, 2003, pp. 1498–1507 (IEEE, USA).

Ó SAGE Publications Ltd 2011

Proc. IMechE Vol. 225 Part I: J. Systems and Control Engineering Downloaded from pii.sagepub.com at STAFFORDSHIRE UNIV on September 13, 2011

708

2 Harashima, F. and Suzuki, S. Human Adaptive Mechatronics – Interaction and Intelligence. In Proceedings of the 9th IEEE International Workshop on Advanced motion control, Istanbul, Turkey, 2006, pp. 1–8 (IEEE, USA). 3 Yu, H. Overview of Human Adaptive Mechatronics. In Proceedings of the 9th WSEAS International Conference on Mathematics and computers in business and economics, Bucharest, Romania, 2008, pp. 152–157 (World Scientific and Engineering Academy and Society (WSEAS) Stevens Point, Wisconsin, USA).

H Yu Faculty of Computing, Engineering and Technology, Staffordshire University, Stafford, UK D H Owens Department of Automatic Control and Systems Engineering, The University of Sheffield, Sheffield, UK R M Parkin Intelligent Automation Research Centre, Loughborough University, Loughborough, UK

Proc. IMechE Vol. 225 Part I: J. Systems and Control Engineering Downloaded from pii.sagepub.com at STAFFORDSHIRE UNIV on September 13, 2011

Ó SAGE Publications Ltd 2011