Error-based Feedback Research Articles

Reduced Order Based Active Disturbance Rejection Controller Design with Applications

Active disturbance rejection control (ADRC) has emerged as a well-addressed controller design technique in recent years. It is a suitable replacement for the error-based feedback PID controller design approaches. The ADRC constitutes two controller design techniques: linear active disturbance rejection control (LADRC) and generalized active disturbance rejection control (GADRC). The LADRC design approach requires minimal information about the plant, while in the GADRC approach, detailed information about the plant is needed. For higher-order plants, the design of ADRC controllers and extended state observers may be pretty complex and costlier. So, the performance analysis of the higher order plant becomes difficult. Therefore, to make the controller simpler, it is always advantageous to reduce the controller size. This paper proposes reduced order linear active disturbance rejection control (ROLADRC), and reduced order generalized active disturbance rejection control (ROGADRC) techniques instead of full-order LADRC and GADRC approaches. The stability equation method (SEM) and other widespread model order reduction (MOR) methods are utilized to reduce the order of the plant. Further, ROLADRC and ROGADRC are compared with existing control techniques in the literature. The effectiveness of the proposed scheme is tested on the sun tracker system (STS) for position control and power systems for load frequency control (LFC).

Event-triggered robust tracking control for fractional-order uncertain systems

In this paper, based on event-triggered (ET) mechanisms, the problem of output tracking for a class of fractional-order uncertain systems with order [Formula: see text] is investigated. Owing to the difficulties of measuring system full-state in practice, output tracking error is firstly used to construct an ET condition, which eventually decides whether the current signal should be transmitted. Then, by utilizing the designed error-based feedback controller, some sufficient conditions are presented to ensure that the controlled system output asymptotically tracks the reference signal. Finally, numerical simulations are performed to validate the effectiveness of the theoretical formulation.

Identifying and remedying failures of hazard anticipation in novice drivers

The current paper proposes a novel taxonomy of latent hazard anticipation by distinguishing modal, strategic, tactical, and operational hazard anticipation skills. Novice drivers face an increased risk of being involved in fatal motor vehicle crashes. Research involving both on-road and driving simulator studies suggests that novice drivers are especially poor at anticipating latent hazards. We reviewed and synthesized previous works on hazard anticipation in young drivers. Modal hazard anticipation skills are broader in nature and more applicable to the general traffic, roadway, and environmental conditions, while strategic, tactical, and operational hazard anticipation skills are more scenario-specific and necessary when navigating a potentially safety-critical situation. It is known that error-based feedback training programs can improve both tactical and strategic, but not yet operational and modal hazard anticipation abilities of novice drivers. Future research should explore individual differences in the effectiveness of training interventions for young novice drivers.

General convergence result for continuous-discrete feedback particle filter

ABSTRACT In this paper, we shall discuss the convergence of the continuous-discrete feedback particle filter (FPF) proposed in Yang et al. (2014). The FPF is an interacting system of N particles where the interaction is designed such that the empirical distribution of the particles approximates the posterior distribution by an innovation error-based feedback control structure. Under some assumptions, it is proved that, for a class of functions ϕ and , the estimate of by FPF converges to its optimal estimate in sense, as the number of particles goes to infinity and the numerical approximation error of computing the control input U goes to zero. Furthermore, the bound of the estimation error is also delicately analyzed.

Error-based output tracking for a one-dimensional wave equation with harmonic type disturbance

Abstract In this paper, we consider output tracking for a one-dimensional wave equation, where the boundary disturbances are either collocated or non-collocated with control. The regulated output and the control are supposed to be non-collocated with control, which represents a difficult case for output tracking of PDEs. We apply the trajectory planning approach to design an observer, in terms of tracking error only, to estimate both states of the system and the exosystem from which the disturbances are produced. An error-based feedback control is proposed by solving a standard regulator equation. It is shown that (a) the closed-loop system is uniformly bounded whenever the exosystem is bounded; (b) when the disturbance is zero, the closed-loop is asymptotically stable; and (c) the tracking error converges to zero asymptotically as time goes to infinity. Numerical simulations are performed to validate the effectiveness of the proposed control.

Trajectory Planning Approach to Output Tracking for a 1-D Wave Equation

In this article, we propose a trajectory planning approach to deal with various of the noncollocated configurations of output tracking through a one-dimensional wave equation. We mainly consider two noncollocated configurations: the performance output is noncollocated to the control input and the disturbance is noncollocated to the measurement output. By proper trajectory planning, the noncollocated configurations can be converted into the collocated ones so that the conventional method can be applied. An error-based feedback is proposed to realize the output tracking. Finally, as an application, the output tracking with general harmonic disturbance and reference signal are exemplified. Numerical simulation shows that the proposed approach is very effective.

Latent Hazard Anticipation in Young Drivers: Review and Meta-Analysis of Training Studies

Young drivers are overrepresented in motor vehicle crashes, and are shown to be poorer at anticipating potential threats on the roadway compared with their more experienced peers. Literature demonstrates the effectiveness of driver training programs at improving young drivers’ latent hazard anticipation performance. Various hazard anticipation training studies have been undertaken on different population demographics using different training scenario presentation modes and multiple evaluation testbeds. These error-based feedback training programs (3M) allow trainees to make a mistake, show them how to mediate the mistake, and provide an opportunity to master the target skills. The current meta-analytical review focused on 19 peer-reviewed training studies that utilized eye movements to measure improvements in drivers’ latent hazard anticipation performance following training. The role of four moderating factors (mode of delivery – PC-based or non PC-based; presentation of training – egocentric or exocentric; method of evaluation – on-road or driving simulator; and age of sample – teen novices aged 16–17 or young drivers aged 18–21) on the training effects were explored. Overall, the current meta-analysis suggest that: (a) superficial improvements in training programs does not necessarily further improve the drivers’ latent hazard anticipation; (b) drivers who completed a training program with both egocentric and exocentric training views achieved greater levels of latent hazard anticipation performance than those who completed a training program that contained either view, but not both; and (c) the effect sizes of the 3M-based training programs on latent hazard anticipation were greater for drivers aged 18–21 years than drivers aged 16–17.

Probabilistic Data Association-Feedback Particle Filter for Multiple Target Tracking Applications

This paper is concerned with the problem of tracking single or multiple targets with multiple nontarget-specific observations (measurements). For such filtering problems with data association uncertainty, a novel feedback control-based particle filter algorithm is introduced. The algorithm is referred to as the probabilistic data association-feedback particle filter (PDA-FPF). The proposed filter is shown to represent a generalization—to the nonlinear non-Gaussian case—of the classical Kalman filter-based probabilistic data association filter (PDAF). One remarkable conclusion is that the proposed PDA-FPF algorithm retains the error-based feedback structure of the classical PDAF algorithm, even in the nonlinear non-Gaussian case. The theoretical results are illustrated with the aid of numerical examples motivated by multiple target tracking (MTT) applications.

Compensation for a lip-tube perturbation in 4-year-olds: Articulatory, acoustic, and perceptual data analyzed in comparison with adults

The nature of the speech goal in children was investigated in a study of compensation strategies for a lip-tube perturbation. Acoustic, articulatory, and perceptual analyses of the vowels /y/ and /u/ produced by ten 4-year-old French speakers and ten adult French speakers were conducted under two conditions: normal and with a large tube inserted between the lips. Ultrasound and acoustic recordings of isolated vowels were made in the normal condition before any perturbation, for each of the trials in the perturbed condition, and in the normal condition after the perturbed trials. Data revealed that adult participants moved their tongues in the perturbed condition more than children did. The perturbation was generally at least partly compensated for during the perturbed trials in adults, but children did not show a typical learning effect. In particular, unsystematic improvements were observed during the sequence of perturbed trials, and after-effects were not clear in the articulatory domain. This suggests that children may establish associative links between multisensory phonemic representations and articulatory maneuvers, but those links may mainly rely on trial-to-trial, error-based feedback correction mechanisms rather than on the internal model of the speech production apparatus, as they are in adults.

Delayed feedback during sensorimotor learning selectively disrupts adaptation but not strategy use.

In sensorimotor adaptation tasks, feedback delays can cause significant reductions in the rate of learning. This constraint is puzzling given that many skilled behaviors have inherently long delays (e.g., hitting a golf ball). One difference in these task domains is that adaptation is primarily driven by error-based feedback, whereas skilled performance may also rely to a large extent on outcome-based feedback. This difference suggests that error- and outcome-based feedback may engage different learning processes, and these processes may be associated with different temporal constraints. We tested this hypothesis in a visuomotor adaptation task. Error feedback was indicated by the terminal position of a cursor, while outcome feedback was indicated by points. In separate groups of participants, the two feedback signals were presented immediately at the end of the movement, after a delay, or with just the error feedback delayed. Participants learned to counter the rotation in a similar manner regardless of feedback delay. However, the aftereffect, an indicator of implicit motor adaptation, was attenuated with delayed error feedback, consistent with the hypothesis that a different learning process supports performance under delay. We tested this by employing a task that dissociates the contribution of explicit strategies and implicit adaptation. We find that explicit aiming strategies contribute to the majority of the learning curve, regardless of delay; however, implicit learning, measured over the course of learning and by aftereffects, was significantly attenuated with delayed error-based feedback. These experiments offer new insight into the temporal constraints associated with different motor learning processes.

Effective reinforcement learning following cerebellar damage requires a balance between exploration and motor noise.

Reinforcement and error-based processes are essential for motor learning, with the cerebellum thought to be required only for the error-based mechanism. Here we examined learning and retention of a reaching skill under both processes. Control subjects learned similarly from reinforcement and error-based feedback, but showed much better retention under reinforcement. To apply reinforcement to cerebellar patients, we developed a closed-loop reinforcement schedule in which task difficulty was controlled based on recent performance. This schedule produced substantial learning in cerebellar patients and controls. Cerebellar patients varied in their learning under reinforcement but fully retained what was learned. In contrast, they showed complete lack of retention in error-based learning. We developed a mechanistic model of the reinforcement task and found that learning depended on a balance between exploration variability and motor noise. While the cerebellar and control groups had similar exploration variability, the patients had greater motor noise and hence learned less. Our results suggest that cerebellar damage indirectly impairs reinforcement learning by increasing motor noise, but does not interfere with the reinforcement mechanism itself. Therefore, reinforcement can be used to learn and retain novel skills, but optimal reinforcement learning requires a balance between exploration variability and motor noise.

Feasibility of error-based electrotactile and auditive feedback in prosthetic walking

Several studies have shown that feedback in upper-leg prostheses is possible, but slow or difficult to interpret. In this study, electrotactile and auditive error-based feedback, only giving feedback when an undesired event occurs, were tested for its use in upper-leg prosthesis when provided during a perturbation. A total of nine healthy subjects walked on a prosthetic simulator which was disturbed at the end of the swing phase. They received either no feedback, electrotactile feedback, or auditive feedback at the time of the perturbation. The reaction time of the subjects only improved by 40 ms when using auditory feedback, compared to the no-feedback condition. No changes in reaction time were found in the electrotactile feedback condition. Considering perturbation detection was not taken into account in this study, this improvement is not enough for practical applications in upper-leg prosthesis. Many transfemoral amputees are insecure about their prosthesis, are afraid of falling, or actually fall. Providing feedback specifically during a perturbation may prevent them from falling, or at least give them a chance to react.

The Effect of Insight and Error-Based Feedback on Young Drivers' following Behavior and Confidence

Young drivers are known to perform less than ideally in a number of traffic contexts. Behavior feedback is critical for the development of safe driving skills. Forty-two young drivers aged 18 to 20 were randomly assigned to three training conditions: an insight and error training condition, an error only training condition, or a control condition. Participants in the training conditions drove simulated trials in which a lead vehicle braked suddenly in front of them. The insight + error group received verbal performance feedback, while the error only group did not. The insight + error group showed a significant increase in time headway by the end of training. However, the increase was not significant in the follow-up drive one week later. Overall driver confidence was also not affected by the training. Results suggest that the combination of insight and error-based feedback modulates behavior over short time periods, but may not be sufficient for the adoption of safe behaviors over longer time periods.

Sliding Control of Force Reflecting Teleoperation:Preliminary Studies

In this paper, sliding mode nonlinear control is applied to force reflecting teleoperation. Various forms of the sliding mode control law are derived for force feedback master manipulation with an arbitrary factor for force and position scaling. Experiments were performed on a one axis test system and frequency domain Hybrid 2-port matrices are measured and compared between the sliding mode controller and a classical position error-based feedback controller. Time domain experiments are also performed. The model-based portion of the sliding mode controller was shown to be responsible for most of its performance improvement, but the nonlinear “sliding” component was essential for steady-state position accuracy and robust stability.