Switching adaptive control of a bioassistive exoskeleton

The effectiveness of existing control designs for bioassistive, exoskeletal devices, especially in highly uncertain working environments, depends on the degree of certainty associated with the overall system model. Of particular concern is the robustness of a control design to large-bandwidth exogenous disturbances, time delays in the sensor and actuator loops, and kinematic and inertial variability across the population of likely users. In this study, we propose an adaptive control framework for robotic exoskeletons that uses a low-pass filter structure in the feedback channel to decouple the estimation loop from the control loop. The design facilitates a significant increase in the rate of estimation and adaptation, without a corresponding loss of robustness. In particular, the control implementation is tolerant of time delays in the control loop and maintains clean control channels even in the presence of measurement noise. Tuning of the filter also allows for shaping the nominal response and enhancing the time-delay margin. Importantly, the proposed formulation is independent of detailed model information. The performance of the proposed architecture is demonstrated in simulation for two basic control scenarios, namely, (i) static positioning, for which the predefined desired joint motions are constant; and (ii) command following, where the desired motions are not known a priori and instead inferred using interaction measurements. We consider, in addition, an operating modality in which the control scheme switches between static positioning and command following to facilitate flexible integration of a human operator in the loop. Here, the transition from static positioning to command following is triggered when either the human–machine interaction force at the wrist or the end-effector velocity exceeds the corresponding critical value. The controller switches from command following back to static positioning when both the interaction force and the velocity fall below the corresponding thresholds. This strategy allows for smooth transition between two phases of operation and provides an alternative to an implementation relying on wearable electromyographic sensors

Guaranteed safe switching for switching adaptive control

Adaptive control algorithms may not behave well in practice due to discrepancies between the theory and actual practice. The proposed results in this manuscript constitute an effort in providing algorithms which assure more reliable operation in practice. Our emphasis is on algorithms that will be safe in the sense of not permitting destabilizing controllers to be switched in the closed-loop and to prevent wild signal fluctuations to occur. Coping with the connection or possible connection of destabilizing controllers is indeed a daunting task. One of the most intuitive forms of adaptive control, gain scheduling, is an approach to control of non-linear systems which utilizes a family of linear controllers, each of which provides satisfactory control for a different operating point of the system. We provide a mechanism for guaranteeing closed-loop stability over rapid switching between controllers. Our proposed design provides a simplification using only finite number of pre-determined values for the controller gain, where the observer gain is computed via a table look-up method. In comparison to the original gain scheduling design which our procedure builds on, our design achieves similar performance but with much less computational burden. Many multi-controller adaptive switching algorithms do not explicitly rule out the possibility of switching a destabilizing controller into the closed-loop. Even if the new controller is ensured to be stabilizing, performance verification with the new controller is not straightforward. The importance of this arises in iterative identification and control algorithms and multiple model adaptive control (MMAC). We utilize a limited amount of experimental and possibly noisy data obtained from a closed-loop consisting of an existing known stabilizing controller connected to an unknown plant-to infer if the introduction of a prospective controller will stabilize the unknown plant. We propose analysis results in a nonlinear setting and provide data-based tests for verifying the closed-loop stability with the introduction of a new nonlinear controller to replace a linear controller. We also propose verification tools for the closed-loop performance with the introduction of a new stabilizing controller using a limited amount of data obtained from the existing stable closed-loop. The simulation results in different practical scenarios demonstrate efficacy and versatility of our results, and illustrate practicality of our novel data-based tests in addressing an instability problem in adaptive control algorithms

Descriptive And Review Study Adaptive Control Of Nonlinear Systems In Discrete Time

Nowadays, analyzing different control systems is a must for virtually all types of modern industries and factories. Analyzing these control systems allows optimizing and streamlining processes, which in many cases are carried out manually, leading to large errors, delays and costly processes. Continuous-time adaptive control of nonlinear systems has been an area of increasing research activity [1] and globally, regulation and tracking results have been obtained for several types of nonlinear systems [2]. However, the adaptive technique is gradually becoming more dynamic after 25 years of research and experimentation. Important theoretical results on stability and structure have been established. There is still much theoretical work to be done [3]. On the other hand, adaptive control in discrete-time nonlinear systems has received much less attention, in part because of the difficulties associated with the sampled data of nonlinear systems [2]. Thus, it is in some theories where adaptive control laws are implemented admitting the intervening nonlinearities in the real system [4] where investigations about the regulation of the system are created. The purpose of this is to implement a very simple adaptive control law and to check the convergence of the closed loop.  However, Zhongsheng Hou, author of several well-regarded papers proposes a model-free adaptive control approach for a class of discrete-time nonlinear SISO systems with a systematic framework [5]-[6]

On Resilient Control of Nonlinear Systems under Denial-of-Service

We analyze and design a control strategy for nonlinear systems under Denial-of-Service attacks. Based on an ISS-Lyapunov function analysis, we provide a characterization of the maximal percentage of time during which feedback information can be lost without resulting in the instability of the system. Motivated by the presence of a digital channel we consider event-based controllers for which a minimal inter-sampling time is explicitly characterized.Comment: 7 pages, 1 figur

Filtering for nonlinear genetic regulatory networks with stochastic disturbances

In this paper, the filtering problem is investigated for nonlinear genetic regulatory networks with stochastic disturbances and time delays, where the nonlinear function describing the feedback regulation is assumed to satisfy the sector condition, the stochastic perturbation is in the form of a scalar Brownian motion, and the time delays exist in both the translation process and the feedback regulation process. The purpose of the addressed filtering problem is to estimate the true concentrations of the mRNA and protein. Specifically, we are interested in designing a linear filter such that, in the presence of time delays, stochastic disturbances as well as sector nonlinearities, the filtering dynamics of state estimation for the stochastic genetic regulatory network is exponentially mean square stable with a prescribed decay rate lower bound beta. By using the linear matrix inequality (LMI) technique, sufficient conditions are first derived for ensuring the desired filtering performance for the gene regulatory model, and the filter gain is then characterized in terms of the solution to an LMI, which can be easily solved by using standard software packages. A simulation example is exploited in order to illustrate the effectiveness of the proposed design procedures

A graph theoretic approach to input-to-state stability of switched systems

This article deals with input-to-state stability (ISS) of discrete-time switched systems. Given a family of nonlinear systems with exogenous inputs, we present a class of switching signals under which the resulting switched system is ISS. We allow non-ISS systems in the family and our analysis involves graph-theoretic arguments. A weighted digraph is associated to the switched system, and a switching signal is expressed as an infinite walk on this digraph, both in a natural way. Our class of stabilizing switching signals (infinite walks) is periodic in nature and affords simple algorithmic construction.Comment: 14 pages, 1 figur

Stabilizing switching signals: a transition from point-wise to asymptotic conditions

Characterization of classes of switching signals that ensure stability of switched systems occupies a significant portion of the switched systems literature. This article collects a multitude of stabilizing switching signals under an umbrella framework. We achieve this in two steps: Firstly, given a family of systems, possibly containing unstable dynamics, we propose a new and general class of stabilizing switching signals. Secondly, we demonstrate that prior results based on both point-wise and asymptotic characterizations follow our result. This is the first attempt in the switched systems literature where these switching signals are unified under one banner.Comment: 7 page

H ? filtering for stochastic singular fuzzy systems with time-varying delay

This paper considers the H? filtering problem for stochastic singular fuzzy systems with timevarying delay. We assume that the state and measurement are corrupted by stochastic uncertain exogenous disturbance and that the system dynamic is modeled by Ito-type stochastic differential equations. Based on an auxiliary vector and an integral inequality, a set of delay-dependent sufficient conditions is established, which ensures that the filtering error system is e?t - weighted integral input-to-state stable in mean (iISSiM). A fuzzy filter is designed such that the filtering error system is impulse-free, e?t -weighted iISSiM and the H? attenuation level from disturbance to estimation error is belowa prescribed scalar.Aset of sufficient conditions for the solvability of the H? filtering problem is obtained in terms of a new type of Lyapunov function and a set of linear matrix inequalities. Simulation examples are provided to illustrate the effectiveness of the proposed filtering approach developed in this paper