This paper presents an integration of two significant targets, i.e., reducing the output impedance and the vibration at the trajectory tracking, into one variable stiffness actuator (VSA) system. The VSA is operated within the cascade impedance control framework, in which the inner torque control loop is designed with the unknown input observer (UIO). The gain-scheduled UIO cooperates with the low and high physical stiffness of the VSA to achieve the low-output impedance and steady trajectory tracking, respectively. The rationality of these implementations is presented considering the stiffness constant and the performance of the control system. The VSA and the gain scheduling-based variable impedance control follow the paradigm of the continuous variable impedance task. In accordance with the knee joint torque, the low and high impedance task with the enhanced performance are applied to a knee exoskeleton with the VSA joint. The effectiveness of the controllers is experimentally verified on a VSA prototype and the exoskeleton with the test person. The robust stability and passivity of the whole control system with the bounded parameter variation rate are investigated.

The cascade impedance control (CIC) is a well-known architecture framework for rehabilitation exoskeleton with compliant joint (e.g., a series elastic actuator). The cascaded position–torque–velocity control loop of the CIC system can deal with specific issues, such as stiction or the accuracy of output impedance. In this article, the control loops of the CIC are extended by the traditional iterative learning control (ILC), and then we examine and compare three types of frameworks, namely, torque learning, impedance learning, and trajectory learning. Their advantages, such as reducing the lag of the output trajectory with a low-gain impedance controller (safety), are discovered. Furthermore, the exoskeleton system is upgraded with the ability of variable impedance. In this part, a fuzzy logic system is proposed. This system uses the electromyography (EMG) signals of the subject and the exoskeleton torque as input, and the decisions on the variable impedance as output. The experiment verifies that the proposed algorithm can effectively decrease the impedance of the exoskeleton when detecting a spasticity from the subject and can maintain the original dynamics of the system when the subject performs a normal movement. Afterward, the effectiveness of the fuzzy logic system together with the ILC-based CIC is experimentally verified in the case of subject–exoskeleton collaborative.

Electric bicycles provide an electric supportive power in addition to the physiological pedalling power of the driver. Electric bicycles thus allow for activities like group rides with people having different degrees of physical fitness. In a group ride, however, each driver would need to adapt the level of electromotive support power (i.e. the assistance level) to the desired level of physiological power output. To overcome this disadvantage, a novel control strategy to automatically adjust the assistance level of the electric bicycle is presented. By this, a uniform velocity can be achieved for all electrical bicycles, while every cyclist applies the amount of power they are most comfortable with. A distributed control approach over a network of electric bicycles is proposed. A reference velocity is calculated by a consensus algorithm. The reference velocity is then used in a local inner feedback loop to adjust the output torque of the support motor. For the velocity feedback loop an H∞-controller is designed. The control algorithms are tested with respect to stability and performance in simulation and experiments. Moreover, local and global stability are established by formal methods.

This article investigates a closed-loop torque-controlled variable stiffness actuator (VSA) combined with a disturbance observer for enhancing low output impedance. We implement the generalized extended state observer (GESO) for conveniently testing the stability of the time-varying VSA system. In our application, the GESO is also required to serve the operation of the low- and high-impedance task. Here, the most important aspect is to consider the influence of the physical stiffness on the output impedance, because the VSA has been regulated with the closed-loop torque control. Through the interaction-torque experiments, we verify that using the fast dynamics GESO with the low-stiffness actuator can achieve low output impedance and stable interaction under the reachable frequency of a human. These properties contribute to perform the low-impedance task. When performing the high-impedance task, where a large torque command is needed, the high-stiffness actuator and the slow dynamics GESO are implemented to achieve high bandwidth and proper tracking performance. The continuously variable observer responses in accordance with the stiffness values are achieved via the gain-scheduling control. Moreover, the present closed-loop linear parameter varying system can be verified to be quadratically stable. The VSA system is then implemented on a knee exoskeleton for a sit-to-stand application. The reference command of the exoskeleton is a joint torque, calculated from the inverse dynamics. This torque signal is also used as the reference command of the stiffness motor of the VSA. The effectiveness of the exoskeleton system is experimentally verified with one healthy volunteer. Subsequently, another two healthy volunteers also successfully experienced the system.

The distance that an electrically powered bicycle can cover depends on factors such as the route’s elevation profile, the motor support selected, and the fitness of the cyclist. This fact requires the cyclist to estimate which motor support may be chosen to reach the goal with the battery’s current state of charge. For this reason, we propose a battery management control system based on a nonlinear model predictive controller (NMPC) for pedal-electric drive units (Pedelecs) that takes into account route information and cyclist fatigue. The goal is to guarantee a user-defined state of charge (SoC) at the end of the route while minimizing cyclist fatigue. The degree of support of the Pedelec is considered as the manipulated variable. In order to find an optimal level of assistance, the NMPC minimizes a quadratic cost function that is subject to three nonlinear distance-dependent models. The first two models describe the bicycle dynamics and the discharge behavior of the battery. To obtain an estimate of the maximum voluntary force that the cyclist can apply, the third model describes the cyclist’s fatigue. The identified models and the control strategy are validated with a trekking Pedelec on a 33km test track. The proposed NMPC is able to guarantee a predefined target SoC at the end of the track while keeping the estimated cyclist’s fatigue low.

We present a framework for achieving a robust stability test of the variable stiffness actuator (VSA) exoskeleton programmed with the gain scheduling-based variable impedance control (GSVIC). In this brief, the focused impedance control framework involves the cascaded position torque control loop, in which both control loops are closed, and the index of the GSVIC is related to the joint torque of the human. However, there is a lack of research on the variation rate of such a biofeedback signal. This lack of information is necessary when performing the robust stability test of the linear parameter-varying (LPV) system. To acquire a bounded variation rate, the mechanical stiffness variation component of the VSA is used to transfer the biofeedback information into the GSVIC. In this case, the LPV system has only one variable parameter with the known and bounded variation rate, i.e., the physical stiffness of the VSA. The operating range of the impedance controller, determined from the test of robust stability via parameter-dependent Lyapunov functions, can meet our application requirements. The whole control system follows the paradigm of the variable impedance task in accordance with human intention. The effectiveness of the control scheme is experimentally verified on a VSA prototype and two subjects wearing the VSA exoskeleton.

In this paper we develop a method to find the passivating parameter space for transfer function matrices with symbolic parameters. The method is subsequently applied to the mechanical-rotary variable impedance actuator (MeRIA), which belongs to the class of variable impedance actuators. The impedance control framework of MeRIA consists of cascaded control-loops guaranteeing a passive (positive real) load transfer function. We therefore focus on finding a robust impedance controller space by employing recursive parameter space testing with respect to the corresponding transfer function. Computed parameter spaces for the corresponding port function and simulations underline the performance of the algorithm.

We present a novel approach to the reconstruction of the physical pedalling torque in an electrically powered bicycle. The external force due to the road slope that is acting on the bicycle is estimated employing the reconstruction of the inclination angle with an orthogonal filter. This orthogonal filter uses an adaptive weighting between gyroscope and accelerometer sensor data. The applied weighting function is based on the bicycle’s acceleration, estimated from a bicycle velocity sensor. By employing a nonlinear physical model of the bicycle, the cyclist’s pedalling torque is reconstructed with an Unscented Kalman Filter. Experimental results from the inclination angle estimator and virtual torque sensor for different road slopes underline the performance of the proposed approach.

We present a novel application of the variable stiffness actuator (VSA)-based assistance/rehabilitation robot-featured impedance control using a cascaded position torque control loop. The robot follows the adaptive impedance control paradigm, thereby achieving an adaptive assistance level according to human joint torque. The feedforward human joint torque command is used to cooperatively adjust the impedance controller and the stiffness trajectory of the VSA (this functional architecture is referred to as the cooperative control framework). In this way, the task performance during movement training can be improved regarding: 1) safety-for example, when the subject intends to contribute considerable effort, low-gain impedance control is activated with a low stiffness actuator to further decrease output impedance and 2) tracking performance-for example, for the subject with less effort, high-gain impedance control is used while pursuing high stiffness to enhance the torque bandwidth. Regarding the safety aspect, we demonstrate that the torque controller designed at low stiffness can be sensitive to the disturbance for low output impedance while maintaining tracking performance. A precondition for this is to treat the input disturbance separately. This is guaranteed by our previously proposed torque control of the VSA using the linear quadratic Gaussian technique. This approach is also employed here, but with additional discussion on the observer design to serve the proposed cooperative control approach. Here, the effectiveness of the proposed control system is experimentally verified using a VSA prototype and a one-degree-of-freedom lower limb exoskeleton worn by a human test person. Note to Practitioners-Control of “physical human-robot interaction” can be achieved by the mechanical parts of the variable stiffness actuator (VSA). However, the mechanical construction for stiffness variation may limit the capacity to achieve low output stiffness and fast stiffness variation in speed. These limitations may become more evident in the assistance/rehabilitation robot applications. To overcome these limitations, the impedance control scheme can be employed to achieve a programmable impedance range and impedance variation speed. This control scheme has been widely applied on the fixed-compliance joint but lacks a way to be implemented on the VSA joint because of its existing capacity to control the impedance with the mechanical construction. This article presents a novel application of the impedance-controlled VSA used on a lower limb robot. We describe how to adjust the actuator stiffness to cooperatively work with the adaptive impedance control scheme. Based on our approach, the robot with the impedance-controlled VSA joint can extend the capacity of bandwidth and low output impedance. This is an improvement on the impedance-controlled fixed-compliance joint. The cooperative control framework presented here was tested on an exoskeleton system with two healthy test persons and is also applicable to other actuator prototypes. Future research aims to employ this system for actual patient training.

Compliant actuators have been increasingly used for active joints in lower-limb exoskeletons or orthoses because they help to guarantee a safe human interaction. One example of such compliant motors is the variable stiffness actuator (VSA). The design of a torque controller for such an actuator is a crucial task in order to provide patients with physical gait assistance and overcome the mechanical limitations of the VSA. Our goal is to implement a torque controller for our mechanical-rotary variable impedance actuator (MeRIA) used in future lower-limb exoskeletons. In the torque control design, we derive a gain-scheduled controller for the polytopic linear parameter-varying (LPV) model of the actuator. This controller is based on the classical H∞ loop-shaping approach. Measurements on the hardware-in-the-loop system in time and frequency domain show that the designed controller provides adequate performance over the whole varying stiffness range. Additionally, the controller provides H∞ robustness with respect to coprime factor uncertainty for the polytopic system. Thus, the torque controller fulfills major safety requirements, and can further be used for human-in-the-loop tests and applications with a lower-limb exoskeleton.

BACKGROUND AND OBJECTIVE:We hypothesized that a biophysical computational model implemented in an object-oriented modeling language (OOML) would provide physiological information and simulative data to study the development and treatment of cardiogenic pulmonary congestion. METHODS:This work is based on the object-oriented cardiopulmonary interaction introduced in [1]. This paper describes the novel model components required to study cardiogenic pulmonary congestion: i) interstitial fluid exchange related to the Starling equation, ii) the lymphatic pump, and iii) the interconnection of these elements with the original cardiopulmonary model. The presented model succeeds in i) describing lymphatic flow at the capillary artery and venous end, ii) activation of the lymphatic pump at elevated pulmonary pressures, and iii) the simulation of the different safety factors related to lung tissue, osmotic gradient, and the lymphatic system during the development of lung congestion. RESULTS:Simulations show a qualitative correlation between model behavior and physiological data from literature. The model also demonstrates the beneficial effect of continuous positive airway pressure therapy on fluid clearance and respiratory mechanics. CONCLUSION:This study demonstrates the successful use of OOML to describe the development of cardiogenic congestion by introducing a model of the lymphatic system and the thoracic fluid balance system, as well as connecting them to the existing cardiopulmonary model.

We present a nonlinear feedback controller design for a variable stiffness actuator, that will force the closed-loop system to a stable limit cycle. The controller design synthesis allows for an inherent selection of limit cycle parameters, such as frequency and magnitude. The controller is based on the central pattern generator (CPG), that is a collection of neurons in the spinal cord of vertebrates and is used to control rhythmic movement, like, for example, breathing and walking. We develop a CPG impedance controller for our variable stiffness actuator MeRIA and validate it in an electromechanical test-bench environment. During these tests, the series elastic element of the actuator was changed in resemblance to the stiffness changes of the muscle-tendon system of vertebrates. Results on CPG controller performance under variable stiffness of the actuator are presented.

Variable impedance actuators are widely used in tasks with an interaction between human and machine. In this paper, a mechanical-rotary variable impedance actuator (MeRIA), designed for knee or hip joint of a lower limb exoskeleton, is investigated. In the torque control loop of the MeRIA, a zero-torque controller is designed to achieve a low output impedance. This control strategy is based on a PI-controller and extended by a disturbance observer (DO). To obtain a LTI transfer function for the DO, the parameter-varying model of the actuator is set to a fixed operating point in terms of the stiffness. The purpose of designing the DO is to enhance the performance of the low-output impedance. Experiments show that the interaction torque between machine and human can significantly be reduced when applying the DO.

The human insulin-glucose metabolism is a time-varying process, which is partly caused by the changing insulin sensitivity of the body. This insulin sensitivity follows a circadian rhythm and its effects should be anticipated by any automated insulin delivery system. This paper presents an extension of our previous work on automated insulin delivery by developing a controller suitable for humans with Type 1 Diabetes Mellitus. Furthermore, we enhance the controller with a new kernel function for the Gaussian Process and deal with noisy measurements, as well as, the noisy training data for the Gaussian Process, arising therefrom. This enables us to move the proposed control algorithm, a combination of Model Predictive Controller and a Gaussian Process, closer towards clinical application. Simulation results on the University of Virginia/Padova FDA-accepted metabolic simulator are presented for a meal schedule with random carbohydrate sizes and random times of carbohydrate uptake to show the performance of the proposed control scheme.

Series elastic actuators decouple stiff motors and gear trains from the load by an mechanic elastic element. This elastic element can be used as torque sensor, acts as an energy storage, decouples the actuator from exogenous high frequency excitation and contributes towards shock resistance and safety in human–robot interaction scenarios. A series elastic element, however, fundamentally limits the achievable actuator bandwidth. Variable stiffness actuators (VSA) were introduced to overcome bandwidth limitations in series elastic actuators and to provide the flexibility necessary for energy efficient operation. The variable elastic element, however, complicates the design of torque and impedance controllers, which have to be synthesised by employing contradicting design objectives, such as minimisation of the output impedance, robust stability and performance. To overcome these synthesis problems, we present a new controller design procedure that imposes a positive real constraint on the load output port function to guarantee a stable interaction with respect to a passive, yet otherwise unknown environment. Additional design requirements are subsequently cast into a generalised plant. A H∞ design procedure is employed to design a gain-scheduled torque controller, which adapts to the varying mechanical stiffness of the actuator. It is then extended with a new procedure for the parametrisation of a superimposed impedance control-loop. The space of parameters for the impedance controller is determined in such way that it guarantees a positive real actuator output port function. The control strategy is tested in an in silico environment and in experiments on a test-bench with the Mechanical-Rotary Impedance Actuator (MeRIA).

Background and objective: This work introduces an object-oriented computational model to study cardiopulmonary interactions in humans. Methods: Modeling was performed in object-oriented programing language Matlab Simscape, where model components are connected with each other through physical connections. Constitutive and phenomenological equations of model elements are implemented based on their non-linear pressure-volume or pressure-flow relationship. The model includes more than 30 physiological compartments, which belong either to the cardiovascular or respiratory system. The model considers non-linear behaviors of veins, pulmonary capillaries, collapsible airways, alveoli, and the chest wall. Model parameters were derisved based on literature values. Model validation was performed by comparing simulation results with clinical and animal data reported in literature. Results: The model is able to provide quantitative values of alveolar, pleural, interstitial, aortic and ventricular pressures, as well as heart and lung volumes during spontaneous breathing and mechanical ventilation. Results of baseline simulation demonstrate the consistency of the assigned parameters. Simulation results during mechanical ventilation with PEEP trials can be directly compared with animal and clinical data given in literature. Conclusions: Object-oriented programming languages can be used to model interconnected systems including model non-linearities. The model provides a useful tool to investigate cardiopulmonary activity during spontaneous breathing and mechanical ventilation. (C) 2018 Elsevier B.V. All rights reserved.

A variable stiffness actuator (VSA) is an inherently parameter-dependent system due to the controllable stiffness element. Within the torque-controlled framework, the VSA is distinguished from the classical series elastic actuator (SEA). A frozen torque controller can directly determine the SEA performance with a fixed-stiffness spring selection. However, since the VSA operates at a set of operating points, the aim is to achieve an adaptive control approach. For this, we propose a gain-scheduled torque controller. The control performance is expected to recover robustness when stiffness values are varied from smaller to larger ones. Simultaneously the bandwidth is maximized, taking into account hardware limitations. In this way, a good tradeoff between stability and performance can be achieved. A key step in the gain-scheduled controller design is to implement the linear controllers, where the linear quadratic Gaussian (LQG) technique was applied to deal with the multiloop feedback (a cascade control scheme) in the VSA plant. A lever-arm based VSA [i.e., a mechanical-rotary variable impedance actuator (MeRIA)] was used to verify this new controller design approach by the simulations and experiments. The resulting gain-scheduled controller was also evaluated by taking into account the impedance control testing on a motion-supported platform for the knee joint.

We present a novel approach to the selection of dynamic system models with regard to stabilisability in terms of their observer error dynamics. For that, we introduce the gap metric for the observer error dynamics as a distance measure. Models are selected for different subsets in such a way, that the gap metric is minimised. The procedure is subsequently applied to classify parametrised Göttingen Minipig models, which were obtained from animal experimental data, into different subsets. These obtained classes are then set up as the basis for an optimal experimental design procedure and result in improved convergence properties, as well as, in reduced implementation effort.

This work introduces a novel technical extension of the Forced Oscillation Technique (FOT) by measuring the respiratory impedance over the whole lung volume at different frequencies. This method proposes a new measurement protocol in which patients breathe slowly from residual volume to total lung capacity, while oscillations are applied simultaneously on the spontaneous breathing. The respiratory impedance Z, computed by means of the windowed cosine fitting method, is frequency- and volume-dependent. The impedance-volume diagram was introduced as a diagnostic tool for abnormalities in lung mechanics. Data were obtained from healthy volunteers and volunteers with mild asthma. The volume-dependency of the respiratory impedance could be clearly observed in all data. In healthy subject, the respiratory resistance (the real part of Z) was maximum at the lowest lung volume and decreases at higher lung level, while the respiratory reactance (the imaginary part of Z) remain constant over a wide range of lung volume. Least-squares parameter estimation was performed on the data for the extended-RIC and the constant-phase models. As a result, both models failed in describing the volume-dependency of Z. Two new extended models were proposed for a better fit of the data: the volume-dependent extended-RIC and the volume-dependent Mead’s models. Overall, the volume-dependent Mead’s model yielded the smallest estimation error. Fig 1: The impedance-volume diagram