Unmatched Ones Research Articles

Light but fruitful: enhanced fuzzy inference via weight-guided selection of rules with attribute weights

Inference using fuzzy rules enables decision-making that is supported with imprecise knowledge. Unlike conventional fuzzy reasoning approaches which directly perform pattern-matching in response to an input observation, recent techniques have integrated rule-firing-based and rule interpolating-based inference methods. This is in order to address challenging issues where observations are of different matching degrees to the rules within a given rule base, including unmatched ones. While applied generally, such a unified inference mechanism may become too complex to exploit the entire rule base for deriving a reasonable conclusion. In practice, only a small number of ‘appropriate’ rules are selected to accomplish the required inference. This paper presents an enhanced integrated fuzzy inference mechanism, which is fed with fewer rules returned by a weight-guided selection procedure. In particular, the weights of rule attributes are utilised in a dual manner: guiding the selection of appropriate rules for rule firing and determining the nearest neighbouring rules for rule interpolation. The resulting mechanism is applied to a real-world problem, empirically demonstrating its significant efficacy.

Compound tracking control based on MPC for quadrotors with disturbances

In this paper, a compound control strategy is proposed to realize the trajectory tracking task of quadrotors under operating constraints and disturbances. Disturbances caused by model uncertainties, environmental noises, and measurement disturbances are divided into matched disturbances and unmatched ones, which are compensated and suppressed separately by using two control components. The integral sliding mode control component is designed to actively reject the matched disturbances, and the control system is then transformed into an equivalent control system subject to equivalent disturbances only related to the unmatched disturbances. The remaining equivalent disturbances are treated by a robust model predictive control component based on the idea of constraints tightening, which minimizes the tracking error in an optimization framework and takes both state and input constraints into account explicitly. The derived compound control strategy is based on these two control components. Conditions are provided to guarantee the robust constraint satisfaction, recursive feasibility and closed-loop stability of the tracking error system. An illustrative example on the quadrotors shows the efficiency and robustness of this compound tracking control algorithm.

Weakly Supervised Video Moment Localization with Contrastive Negative Sample Mining

Video moment localization aims at localizing the video segments which are most related to the given free-form natural language query. The weakly supervised setting, where only video level description is available during training, is getting more and more attention due to its lower annotation cost. Prior weakly supervised methods mainly use sliding windows to generate temporal proposals, which are independent of video content and low quality, and train the model to distinguish matched video-query pairs and unmatched ones collected from different videos, while neglecting what the model needs is to distinguish the unaligned segments within the video. In this work, we propose a novel weakly supervised solution by introducing Contrastive Negative sample Mining (CNM). Specifically, we use a learnable Gaussian mask to generate positive samples, highlighting the video frames most related to the query, and consider other frames of the video and the whole video as easy and hard negative samples respectively. We then train our network with the Intra-Video Contrastive loss to make our positive and negative samples more discriminative. Our method has two advantages: (1) Our proposal generation process with a learnable Gaussian mask is more efficient and makes our positive sample higher quality. (2) The more difficult intra-video negative samples enable our model to distinguish highly confusing scenes. Experiments on two datasets show the effectiveness of our method. Code can be found at https://github.com/minghangz/cnm.

A new robust output feedback control for a class of uncertain nonlinear systems

This paper presents studies on a robust adaptive output feedback stabilisation for a class of nonlinear systems, which is subjected to parametric uncertainties and disturbances. The disturbances are considered to be general, i.e. both the matched and unmatched ones are present. A novel robust adaptive control is developed for this problem. A technique is employed to avoid the difficulty in handling the nonlinear gain functions associated with the disturbances. For this, a new Lemma is obtained to handle the nonlinear functions that simplify the controller derivation steps. The unknown parameters and disturbances are tackled by deriving the tuning functions using a backstepping design. Finally, simulation is carried out to validate and show the effectiveness of the proposed robust controller.

Robust Motion Control Architecture for an Upper-Limb Rehabilitation Exosuit

Upper-limb exosuits are light wearable devices suitable for applications such as rehabilitation or assistance in industrial environments. One of the main drawbacks of these systems is the amount of uncertainties intrinsic to the nature of the device. Moreover, the direct interaction between the exosuit and its user adds disturbances to the system. Therefore, a robust control architecture to these phenomena is required for its appropriate control. In this article, a robust motion (position and speed) control architecture based on a cascade proportional-integral (PI) and a sliding mode controller (SMC), and a nonlinear disturbance observer (NDO) for the upper-limb cable-driven rehabilitation exosuit LUXBIT is designed. We call the proposed controller by the acronym CPISDO. The SMC nature allows to compensate the matched disturbances and uncertainties, while the NDO counteracts the unmatched ones. The PI component helps in reducing tracking error. Dynamic modelling, system architecture and control design are addressed. The CPISDO controller has been implemented over the exosuit and several experiments have been performed over 10 healthy subjects to evaluate the controller’s tracking performance as well as the disturbance rejection. Supertwisting (a state-of-the-art SMC) and PI controllers have been implemented for CPISDO validation. Results are compared with other state-of-the-art solutions.

Capacity Optimality of AMP in Coded Systems

This paper studies a large random matrix system (LRMS) model involving an arbitrary signal distribution and forward error control (FEC) coding. We establish an area property based on the approximate message passing (AMP) algorithm. Under the assumption that the state evolution for AMP is correct for the coded system, the achievable rate of AMP is analyzed. We prove that AMP achieves the constrained capacity of the LRMS with an arbitrary signal distribution provided that a matching condition is satisfied. As a byproduct, we provide an alternative derivation for the constraint capacity of an LRMS using a proved property of AMP. We discuss realization techniques for the matching principle of binary signaling using irregular low-density parity-check (LDPC) codes and provide related numerical results. We show that the optimized codes demonstrate significantly better performance over un-matched ones under AMP. For quadrature phase shift keying (QPSK) modulation, bit error rate (BER) performance within 1 dB from the constrained capacity limit is observed.

Reconstruction of lines and planes of urban buildings with angle regularization

Three-dimensional reconstruction of line and plane structures from two images is a major task in urban building modeling. However, traditional line segment (LS) matching methods frequently produce inaccurate few LS matches, and further lead to unreliable sparse 3D line-plane reconstruction. To address these issues, this paper presents an effective line-plane reconstruction method based on angle regularization. The proposed method first performs LS matching by learning the angles between planes using convolutional neural networks (CNNs). Angle regularization is used to correct unreliable LS matches and infer progressively potential 3D LSs for unmatched ones. Then, the resulting 3D LSs and planes are globally regularized by incorporating geometric constraints, image features, and plane and angle regularity terms under a unified optimization framework. Experiments on several standard datasets demonstrate that our method has clear advantages over the state-of-the-art methods.

T7 RNA Polymerase Discriminates Correct and Incorrect Nucleoside Triphosphates by Free Energy

RNA polymerase (RNAP) is the primary machine responsible for transcription. Its ability to distinguish between correct (cognate) and incorrect (noncognate) nucleoside triphosphates (NTPs) is important for fidelity control in transcription. In this work, we investigated the substrate selection mechanism of T7 RNAP from the perspective of energetics. The dissociation free energies were determined for matched and unmatched base pairs in the preinsertion complex using the umbrella sampling method. A clear hydrogen-bond-rupture peak is observed in the potential of mean force curve for a matched base pair, whereas no such peaks are present in the position of mean force profiles for unmatched ones. The free-energy barrier could prevent correct substrates from being separated from the active site. Therefore, when NTPs diffuse into the active site, correct ones will stay for chemistry once they establish effective base pairing contacts with the template nucleotide, whereas incorrect ones will be withdrawn from the active site and rejected back to solution. This result provides an important energy evidence for the substrate selection mechanism of RNAP. Then we elucidated energetics and molecular details for correct NTP binding to the active site of the insertion complex. Our observations reveal that strong interactions act on the triphosphate of NTP to constrain its movement, whereas relatively weak interactions serve to position the base in the correct conformation. Triple interactions, hydrophobic contacts from residues M635 and Y639, base stacking from the 3′ RNA terminal nucleotide, and base pairing from the template nucleotide act together to position the NTP base in a catalytically competent conformation. At last, we observed that incorrect NTPs cannot be as well-stabilized as the correct one in the active site when they are misincorporated in the insertion site. It is expected that our work can be helpful for comprehensively understanding details of this basic step in genetic transcription.

SMC Design for Robust Stabilization of Nonlinear Markovian Jump Singular Systems

In this technical note, the sliding-mode control (SMC) problem is investigated for T–S fuzzy-model-based nonlinear Markovian jump singular systems subject to matched/unmatched uncertainties. To accommodate the model characteristics of such a hybrid system, a novel integral-type fuzzy sliding surface is put forward by taking the singular matrix and state-dependent projection matrix into account simultaneously, which is the key contribution of the note. The designed surface contains two important features: 1) local input matrices for different subsystems in the same system mode are allowed to be different; and 2) the matched uncertainties are completely compensated, and the unmatched ones are not amplified during sliding motion. Sufficient conditions for the stochastic admissibility of the corresponding sliding-mode dynamics are presented, and a fuzzy SMC law is constructed to ensure the reaching condition despite uncertainties. The applicability and effectiveness of our approach are verified by simulations on an inverted pendulum system.

Integral Sliding‐Mode Observation and Control for Switched Uncertain Linear Time Invariant Systems: a Robustifying Strategy

AbstractA robustifying methodology for switched systems with matched and unmatched uncertainties/perturbations and autonomous location transitions is presented. We avail of such methodology to design a control strategy based on integral sliding modes, thereby ensuring theoretically exact compensation of the matched uncertainties/perturbations and the minimization of the effects of the unmatched ones. An output integral sliding‐mode control technique, based on a switched algebraic hierarchical observer is also proposed. This approach allows the theoretically exact compensation of the matched uncertainties/perturbations right after the first moment. The proposed approach is illustrated via numerical simulations.

Quasi-minimal active disturbance rejection control of MIMO perturbed linear systems based on differential neural networks and the attractive ellipsoid method

This study addresses the problem of designing an output-based controller to stabilize multi-input multi-output (MIMO) systems in the presence of parametric disturbances as well as uncertainties in the state model and output noise measurements. The controller design includes a linear state transformation which separates uncertainties matched to the control input and the unmatched ones. A differential neural network (DNN) observer produces a nonlinear approximation of the matched perturbation and the unknown states simultaneously in the transformed coordinates. This study proposes the use of the Attractive Ellipsoid Method (AEM) to optimize the gains of the controller and the gain observer in the DNN structure. As a consequence, the obtained control input minimizes the convergence zone for the estimation error. Moreover, the control design uses the estimated disturbance provided by the DNN to obtain a better performance in the stabilization task in comparison with a quasi-minimal output feedback controller based on a Luenberger observer and a sliding mode controller. Numerical results pointed out the advantages obtained by the nonlinear control based on the DNN observer. The first example deals with the stabilization of an academic linear MIMO perturbed system and the second example stabilizes the trajectories of a DC-motor into a predefined operation point.

Asynchronous Networked MPC With ISM for Uncertain Nonlinear Systems

A model-based event-triggered control scheme for nonlinear constrained continuous-time uncertain systems in networked configuration is presented in this paper. It is based on the combined use of model-predictive control (MPC) and integral sliding-mode (ISM) control, and it is oriented to reduce the packet transmission over the network both in the direct path and in the feedback path, in order to avoid network congestion. The key elements of the proposed control scheme are the ISM local control law, the MPC remote controller, a smart sensor, and a smart actuator, both containing a copy of the nominal model of the plant. The role of the ISM control law is to compensate matched uncertainties, without amplifying the unmatched ones. The MPC controller with tightened constraints generates the control component oriented to comply with state and control requirements and is asynchronous since the underlying constrained optimization problem is solved only when a triggering event occurs. In the paper, the robustness properties of the controlled system are theoretically analyzed, proving the regional input-to-state practical stability of the overall control scheme.

Integral Sliding Modes with NonlinearH∞-Control for Time-Varying Minimum-Phase Underactuated Systems with Unmatched Disturbances

This paper presents a methodology for controlling nonlinear time-varying minimum-phase underactuated systems affected by matched and unmatched perturbations. The proposed control structure consists of an integral sliding mode control coupled together with a global nonlinearH∞-control for rejecting vanishing and nonvanishing matched perturbations and for attenuating the unmatched ones, respectively. It is theoretically proven that, using the proposed controller, the origin of the free-disturbance nonlinear system is asymptotically stabilized, while the matched disturbances are rejected whereas theL2-gain of the corresponding nonlinear system with unmatched perturbation is less than a given disturbance attenuation levelγwith respect to a given performance output. The capability of the designed controller is verified through a flexible joint robot manipulator typically affected by both classes of external perturbations. In order to assess the performance of the proposed controller, an existing sliding modes controller based on a nonlinear integral-type sliding surface is also implemented. Both controllers are then compared for trajectory tracking tasks. Numerical simulations show that the proposed approach exhibits better performance.

Output Feedback Control of Underactuated Spacecraft Hovering in Circular Orbit With Radial or In-Track Controller Failure

This paper proposes the output feedback control schemes for underactuated spacecraft hovering without either the radial or the in-track thrust. In contrast to the conventional fully actuated output feedback hovering control that only lacks velocity signals, a new problem is observed in the underactuated case that the simultaneous loss of velocity measurements and thrust does not only result in the loss of velocity information but also gives rise to unknown system parameters’ effects. Furthermore, due to the loss of thrust, the disturbances turn into unmatched ones. To achieve velocity-free hovering control for the underactuated cases, a novel adaptive reduced-order observer is first proposed for the purpose of velocity and parameter estimation. With the estimates provided by the observer, an output feedback controller is then designed by using the inherent coupling of system states. The asymptotic stability of the overall closed-loop system for either case is guaranteed by a Lyapunov-based method. Finally, numerical simulations are presented to demonstrate the feasibility and validity of the proposed controllers for hovering perturbed by the unmatched disturbances with the simultaneous loss of velocity measurements and thrust.

Analysis of microwave interference switches with distributed power of switched wave and plasma gas-discharge switching

This paper reports on development of effective cascade type microwave interference switches using waveguide H-tees providing total transition attenuation value of about -50dB at the non-transmitting state, the power losses of -2-3dB at the transmitting state, and the working power compared to the one of a regular waveguide. These switches have different types of connections of two or three H-tees. Different designs provide different distributions of switched wave power between tees and provide different power levels of the switched wave. Characteristics of the switches made of tees matched from their side arms and of unmatched ones were calculated using the scattering matrix method. It was shown the matched tees used in the design allow decreasing by several times the power level of the switched wave and that increases the operating power and stability of the switching process. While some definite combination of unmatched tees allow increasing the power level of the switched wave and may provide effective switching of the transmitted wave at decreased power level. It was shown experimentally the cascade switches could be used as effective energy extraction device in an active resonant microwave compressor also.

SU‐E‐J‐165: Ghost Marker Prediction, Detection and Elimination in Marker‐Based Optical Tracking Systems

Purpose:In optical tracking system (OTS), ghost marker (GM) limits users' flexibility in marker placement and can lead to incorrect patient setup or system execution failure. This work aims to model the phenomenon of GM and propose robust algorithms for GM prediction, detection and elimination.Methods:Two GMs occur when two markers and two sensors of the OTS are coplanar. However, when one marker gradually moves out of the plane and breaks the coplanar condition, both GMs briefly remain before they completely disappear. To explain this effect, we expanded line‐line intersection definition and the coplanar condition: two lines intersect when their distance is less than threshold Ω and involved points are said to be coplanar within Ω. We fixed one marker and moved the other through the plane with a 0.1 mm step length. Sensor positions were calculated using a back projection method when coplanar condition was strictly satisfied. Ω was determined as line‐line distance when ghost marker first appeared. The prediction algorithm checks whether any two given markers are coplanar with the two sensors within Ω; the detection algorithm checks whether any marker is near the intersection of lines connecting sensors and two other markers. A backtracking pattern matching algorithm matches markers to reference markers and eliminates unmatched ones as GMs. The algorithms were validated with two phantoms and 40 SBRT patients using 5~8 markers.Results:The prediction success rates were 97.7% and 89.6% and the detection success rates were 100% on the two phantoms (1544 ' 2045 samples). The matching success rates were 100% on both phantoms and patients.Conclusion:The proposed model precisely explains the phenomenon of GMs in marker‐based OTS. The proposed detection and matching algorithms guarantee complete elimination of GMs, thus avoiding errors in SBRT tracking and providing user maximum flexibility in marker placement.

Design of the matched chaotic stimulation for fault detection of the single input single output system

In this paper, for the fault detection of a single-input single-output (SISO) system, we define a concept of matching chaotic stimulation with a measured system, establish a criterion of matching chaotic stimulation with a measured system, and propose a method of adjusting the matching of chaotic stimulation with a measured system. Finally, the improved prediction error is used to detect faults in the SISO system. The simulation results show that matched chaotic stimulation can be used to detect faults effectively, while unmatched ones can add uncertainty into the fault detection.

Conventional vs. implant retained overlay dentures: a clinical trial of masseter and anterior temporalis electromyography

Abstract Background: Implant supported overlay dentures (ISODs) have been widely accepted among patients using conventional removable complete dentures (CRCDs). The present study aimed to comparatively study conventional and ISODs in terms of function and coordination of masticatory muscles using electromyograms.Materials and methods: Included were 10 patients with ISODs (each with 2 implants in the intercanine area). The mean wave range (MWR) and frequency (MWF) of masseter and temporalis were recorded with (ISOD) and without (CRCD) ball attachments while maximum clenching on cotton rolls (cotton roll clenching), maximum intercuspal clenching (clenching), and unilateral gum chewing (chewing) using electromyography. Data were analyzed in SPAW using t-paired for matched groups and independent sample t-tests for unmatched ones. Results: MWF differences were not statistically significant with or without attachments (p > 0.05). Without attachments in place, MWF of both masseter and temporalis muscles significantly decreased when patients clenched on cotton rolls (p = 0.01 and 0.02, respectively) and when chewing unilaterally (p = 0.01 both). With attachments present, the right and left temporalis muscles did not show identical mean wave ranges while chewing (p = 0.01). Without attachments, this disharmony was seen in the left and right masseter muscles (p = 0.03). MWR of masseter was higher in men while chewing with attachments (p = 0.02). Without attachments, MWR of temporalis was higher in women while cotton roll clenching (p = 0.03) and chewing (p = 0.02). Conclusion: These findings are seemingly in favor of improved masticatory function and coordination in edentulous patients with the application of ISODs.

Integral Sliding Mode Control for Nonlinear Systems With Matched and Unmatched Perturbations

We consider the problem of designing an integral sliding mode controller to reduce the disturbance terms that act on nonlinear systems with state-dependent drift and input matrix. The general case of both, matched and unmatched disturbances affecting the system is addressed. It is proved that the definition of a suitable sliding manifold and the generation of sliding modes upon it guarantees the minimization of the effect of the disturbance terms, which takes place when the matched disturbances are completely rejected and the unmatched ones are not amplified. A simulation of the proposed technique, applied to a dynamically feedback linearized unicycle, illustrates its effectiveness, even in presence of nonholonomic constraints.

Dynamic switching surfaces for output sliding mode control: An [formula omitted] approach

The robustness properties of sliding-mode and H∞ controllers are exploited to produce a dynamic output feedback controller that is insensitive to matched perturbations and attenuates the unmatched ones. The assumptions on the plant differ from the standard assumptions of the Riccati state-space approach to H∞ control. The sliding-mode controller drives the state into a reduced-order manifold for which the equivalent system does satisfy the standard assumptions and hence the standard theory can be applied. The resulting Riccati equations are of reduced order.