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We analyze the robustness of a system-level genetic circuit which is constructed by a bottom-up strategy. The latest trend in synthetic biology is to create large-scale and complex genetic circuits realizing desired programmable functions. An approach for the creation is bottom-up construction, that is, well-characterized small-scale circuits are coupled into large-scale system-level circuits involving desired programmable functions that can be predicted from the modules. However, in general, an intrinsic property in a circuit may be broken by internally connecting external circuits. We analyze a successful circuit created by a bottom-up construction strategy to identify the reason behind a successful synthesis. Utilizing the robustness analysis method based on the structured singular value, we can guarantee the validity of the bottom-up construction.

The robotics technology is expected to play an important role not only in industries, but also in medicine and welfare. An EMG-controlled artificial arm is one of the most important robotic systems for persons who lost their original arm by accident or disease. This paper presents a concept of the 3DOF intelligent artificial arm that activates the elbow flexion/extension motion, forearm pronation/supination motion, and hand open/close motion based on EMG signals of the user's remained active muscles.

We present a new control law for the problem of docking a wheeled robot at a certain location with a desired heading. Recent research into insect navigation has inspired a solution which uses just one environment sensor: a video camera. The control law is of the “behavioral” or “reactive” type, in that no attempt is made to observe the relative pose of robot and target, all control actions are based on immediate visual information. Knowledge of the distance to the target is not required. Docking success under certain conditions is proved mathematically, and simulation studies show the control law to be robust to camera calibration errors.

Aim of the present work is to design and develop a system of torques generation for a mobile six-legged robot, based on biological inspiration, namely on studies on the stick insect (Carausius morosus). Virtual learning by simulation of kinematics and dynamic is here proposed as test bed of solutions before building the robot. Results confirm the goodness of the evolution learning approach in the design of the hexapod robot, showing good performances very close to nature solutions and efficient in terms of adaptation to environment constraints changes.

This paper deals with the problem of modelling and control of the knee joint dynamics. Using controlled functional electrical stimulation (FES) of the quadriceps muscle group the knee joint will be positioned at a commanded angle, subject to disturbances and displacements of the hip and ankle joints. A simple ARX-model has been estimated directly from measured input-output plant data. Further, a discrete linear pole-placement controller will be presented as solution for the tracking and regulation problems. Advantages of this approach in comparison with nonlinear controllers based on physiological models will be discussed and natural limitations are shown. A simple tuning rule for an already determined controller will be given to achieve robust stability with respect to the plant characteristics, which depend on the actual operating point. Experiments with neurologically intact subjects show encouraging results.

Self-organization of a mechanical structure based on remodeling of living systems is discussed. A mathematical model of adaptive formation is proposed. The model consists of identical mechanical dements which determine their actions by only local information. In this paper, a new biological function by use of L-systems is added to the model and the performance is examined. The computer simulation shows that the proposed m odd activdy changes the topological structure for an unexpected loading force or multiple mechanical conditions.

The paper presents the assumptions of walking machine gait planning method. The gait is planned in real time; in each control step, sensor readings, the machine state and other essential factors are taken into account. In the process of gait planning., the hypothesis that is used assumes two-stage motion planning by the senso-motoric brain system.

The cybernetical analysis of transient responses of the blood pressure control system in man gives essential but not complete system characteristics because of stochastic influences partly originating outside the baroreceptor closed loop. Therefore, we have additionally characterized the stochastic processes quantitatively by spectral analysis.

In manipulator force control, a manipulator arm is in contact with the environment, and contact forces are detected at the end of the manipulator arm by means of a multi-dimensional force-torque sensor system. An active and non-deterministic environment is found in direct manual control situations. Direct manual control is characterized by a high degree of interaction between man and machine. Under certain conditions the total man-machine system becomes unstable or oscillatory. Examples of such systems are servo-assisted teach-in programming of manipulators and heavy-load assistive systems. Based on data from one-dimensional experiments on two Cartesian experimental manipulators in a direct manual control situation, the dynamics of the interaction process is discussed. It is established that the stability of the man-machine system is a function of the position of the operator relative to the manipulator working direction. It is also shown that the dynamics of the human operator in direct manual control is of second order. Finally, an RT-model structure and an invariant controller are proposed to describe the movements of the human arm in a horizontal plane.

This paper describes work in progress toward the application of closed-loop control systems for the functional neuromuscular (electrical) stimulation of muscles in paralyzed patients, for the purpose of restoring walking. Reciprocal walking-like motion is produced in the complete paraplegic patient using a portable microprocessor-controlled electrical stimulation and intramuscular percutaneous electrodes. This open loop system has three operating modes that are initiated by patient command: standing (double support), right-leg forward motion and left-leg forward motion. An in-lab minicomputer-based closed-loop system is being tested for balance control during stance, and trajectory control of the swing leg during forward motion.

Recording biological parameters of the driver, parameters of the car, and parameters of the environment it is possible to calculate the difference between normal safe and less normal less safe driving. This could be proved in case of driving in a tired state with the parameters pulse rate, skin resistance, and steering wheel reversal rate. A method which allows to calculate a normal pattern of driving as a comparing criterion for actual driving condition is proposed using inductive entropy and inductive information.

The human operator represents the limiting system component in risky man-machine systems. The complicated psychophysiological structure of purposeful human activity is the reason not only for the high potential capability of the operator but also for the great variation of his current efficiency. This paper introduces the general application of a multivariate concept in the collection, parametrizing, and evaluation of data in dynamic investigations of the operational competence of operators on the base of aircraft navigation. The examination of pilots during the failure management training on a civil aircraft simulator provides informations on the use of objectively and subjectivly determinable parameters of the psychological, physiological, and performance level for the automated evaluation of present-state competence of operators.

A mathematical model and the analysis procedures based thereon are proposed to evaluate the policy for technological aid to the developing countries. This model may be considered mathematically as a generalization of Lotka-Volterra model, Gause model and Leslie-Gower model and has a more flexibility for stability and sensitivity analysis. This model may be useful in providing a foundation of energy or resource economics as representing the material flow in physical terms. The method proposed here is applicable even when the availability of data is limited and rather provides a tool for parameter estimation by generating various possible trajectories. This method is shown to represent and explain the complicated nonlinear relationship between the developed and developing countries in the decade around the oil-crisis. Hence it is expected useful in predicting the industrial behaviour, classifying the technological qualities in the developing countries and evaluating possible changes of policies.

The increasing applicability of system identification, as noticed in purely-engineering problems, can also be recognized in bio-medical tasks. This development of actual applications takes place in spite of the well-known specific limitations and problems related to such bio-systems: -restricted amount of a priori qualitative Knowledge; -very limited (if any) quantitative knowledge; -nonlinearities; -variability in time of the objects; -variability between objects; -poor measurability/observability; -difficult experimental conditions, as well as limitations due to ethical aspects In this workshop the attention is focussed on the continuing development of (potential) successful applications, with an emphasis on the more recent contributions. Ways of application include situations like: research, diagnosis, medication, surgery, rehabilitation, medical training This paper summarizes a number of pertinent general considerations. The fields of application discussed in this workshop include: - metabolic and endocrine systems - respiratory and cardiovascular systems - neuromuscular systems - sensory systems and neuronal systems One has to realize, of course, that these fields do not constitute an exhaustive list. They are, however, certainly representative for the challenges, feasibilities and limitations in this fascinating domain of human endeavour

The stochastic dynamic model of the conditioned avoidance reflex is considered. The elements of the model are outlined. The problem of identification of this model is solved and algorithm of solution is presented. The algorithm was employed in the identification of the model on the base of real experimental data. Some related results are presented. The model is to be utilized by biologists in analysis of the results of learning experiments.

A mathematical model of the production process of live feed to fish larvae is presented. The model is used as a design tool to construct a constrol system which ensure stable and controlable conditions for live feed organisms (rotifers). The simulation results demonstrate the effect of possible changes inthe biological parameters and different operational routines.

Two key aspects of our approach to identification of endocrine, metabolic and pharmacokinetic systems are presented and applied to experimental studies of thyroid hormone distribution and metabolism dynamics in the rat and human. First, we use unidentifiable but 'parametrically isomorphic' topologies for realistically structuring our models. The additional technical problems introduced by this structuring approach are then partially overcome by introducing additional a priori information, in the form of physico-chemically based inequality constraints, to obtain 'quasi-identiflability,' in special cases, and physiologically or clinically useful parameter space boundaries in general. Second, we use a sequential optimization method for kinetic experiment design, based on an information matrix scheme, that provides maximally accurate models, consistent with usually severe data limitations (a 'small-sample' theory for dynamic systems). Our results to date have uncovered some remarkable similarities in thyroid hormone distribution and metabolism between the laboratory rat and the human species.