Figure 1. Flight muscle system of flies, calcium-activated flight power muscles (A-IFM), and feedback loop for wing control muscles (WCM). (A) Morphology of A-IFM dorsolongitudinal muscle (DLM, 12 fibers) and dorsoventral muscle (DVM, 14 fibers) inside the fly thorax. TTM, tergo-trochanter muscle. (B) Fluorescence signaling of electrically activated A-IFM expressing the calcium probe Cameleon in a resting (C) and flying fruit fly (D). (E) Major wing control muscles at the fly’s wing hinge (b1-3, basalare muscles; I1-2 and III2-4, axillary muscles; side view). (F) Hypothetical feedback loop for activation timing of WCM. Strain-sensitive mechanoreceptors on wings and halteres produce neural spikes (blue) at specific times of the wing stroke cycle (phase-coupled activation). The elementary motion detector (EMD) of the fly’s compound eye converts visual motion into graded potentials (red) that are transmitted via descending visual interneurons to the thoracic ganglion (visual pathway). The three inputs are integrated by a WCM motoneuron (MN; ʃ, integration process), generating a single muscle action potential at the neuron’s threshold (TH) at time ϕ 0 (activation phase)
Studies focusing on speech motor learning tried to answer whether the principles of motor learning affect the speech motor controlsystem in a similar way to the limbs motor controlsystem . One of the most im- portant variables affecting the learning of motor skill is feedback [4, 8]. Feedback is the second most important variable affecting the acquisition of new motor skills . Feedbacks are of two kinds; intrinsic feedback, which includes information provided by internal sources dur- ing or after the movement, and extrinsic feedback, which provides information by an external source [10, 11]. Ex- trinsic feedback can provide information about how the movement is performed and which motor patterns are used for doing it; this is called Knowledge of Perfor- mance (KP) feedback. Extrinsic feedback can also pro- vide information about the result of the motor action and is called the Knowledge of Result (KR) feedback [4, 11]. Several variables related to extrinsic feedback including the frequency and the timing of the feedback are of the researchers’ interests. Feedback can be presented imme- diately after the movement or with a delay . Theoreti- cally, the delay interval before receiving the feedback by providing the opportunity for loss of the memory track- ing helps in forgetting the motor memory. Therefore, it seems that prolongation of the time between movement and feedback can degrade learning . Salmon et al. showed that the delay interval before receiving feedback
Frederickson and Branigan (2005) reported that unpleasurable emotions lead to a narrowing of the scope of attention during cognitive tasks and decrease the thought-action repertoire. It has been reported that participants receiving verbal admonitions have decreased error-related negativity potentials and reduced per- formance compared to control group participants (Ogawa, Masaki, Yamazaki, & Sommer, 2011). In the central nervous system, the striatum, which is a basal nucleus in the brain that may include the amygdala, participates in the forma- tion of memories of kinetic system sequences. Since the basal nuclei of the brain accelerate purposeful movements and control unnecessary movements, move- ment control may be affected if the amygdala is stimulated.
Signals are carried out on mineral insulated cables with copper center conductor and stainless steel cladding (coaxial cable was used in earlier implementations, we have subsequently switched to a triaxial cable to increase signal reliability, see Appendix A). As such, there are multiple uncompensated thermojunctions (e.g., tungsten-rhenium to copper and molybdenum to stainless steel) between the surface thermojunction and the measurement electronics. Use of this system therefore relies on making measurements of the ambient temperature of the thermocouple assembly prior to a discharge. This is performed via ice-point compensated type-K thermocouples embedded in the divertor tiles surrounding the surface thermocouples. The change in signal voltage during the plasma pulse is then attributed to a change in surface thermojunction voltage and thus surface temperature. This is a valid assumption during the discharges in C-Mod, which are too short (<2s) for the other thermojunctions to change temperature. Extension of this system to steady state is discussed in Appendix B. The surface heat flux is digitally computed after each plasma discharge by using the recorded surface temperatures as the boundary condition on 1-D finite element thermal model of the surface thermocouple.
The work principle of the multi station automatic assembly system is shown as the Figure 6. Firstly, the system completes initialization. After that, the load and unload gripper clamps the parts, and the robot moves the parts to the designated position and completes the unloading. Then, the assembly station starts working. The gripper on the assembly module clamping the part moves with the turntable and the Z-axis to the designated position. At the same time, the prism moves out, the light source and camera are opened. Next, the image of the part is captured. In the process of image processing, the prism and light source are reset. After the image processing, the position and orientation of the part is adjusted according to the position deviation, and completes the assembly. Did the last part complete the assembly? If the last one is not assembled, starting the assembly of the next part. When the last part completed the assembly, the assembly module clamps the product and follows the Z-axis and turntable to the initial position. At this moment, the loading and unloading station gripper clamps the product, and the robot moves to the box to complete the unloading.
The structure of the paper is as follows: the next section presents the mass-spring-damper system used in this research and derives the necessary transfer functions. Section three discusses the controller design. A first subsection presents the design of an integer-order PI controller using model-based computer aided design tools. The fractional-order PI controller is designed in the next subsection and is also based on model-based techniques. Section four discusses the performed simulations and the results. It presents the implementation method of fractional-order controllers and two simulations. In the first simulation the FOPI controller is compared to the classical PI controller. A second simulation investigates the robustness to gain variation of the system. A conclusion is formed in the final section.
By means of the desmosterol suppression technique described in the previous paper, the influence of hepatomas on sterol metabolism has been studied in the intact rat. The major finding of this study is that all hepatoma-bearing rats demonstrate a consistent in vivo loss of the cholesterol feedbacksystem that is characteristic of normal liver. The results also
How to control chaos in the economic system has aroused the interest of researchers. We research the chaos control in a new Resource-Economic-Pollution system by time-delayed feedbackcontrol. By determining the appropriate range of time delay τ and feedback strength k, the chaotic phenomena of the system are controlled. We verify the linear stability and the existence of Hopf bifurcation of the system. Numerical simulations show that chaos control can eliminate the chaotic behavior of the system and stabilize the system at the equilibrium point. When the time lag term is in a certain interval, the chaotic phenomenon of the system will disappear and the system will be controlled in a stable state. In practice, due to capacity and financial constraints, the firm or the government often restrains output through many methods to confine the range of fluctuations in these variables. This shows that the government or corporate decision makers have often used this approach consciously or unconsciously to promote steady economic growth.
To examine the effects of feedback frequency on intertemporal choices and the moderating role of reward timing, we collect survey data from 78 middle-level managers working at a Brazilian company. The main contribution of this research to the management and accounting literature on intertemporal choices is twofold. First, little is known about the effect of feedback frequency on intertemporal choices. Bhojraj and Libby (2005) investigate the effect of disclosure frequency of mandatory external report on myopic behavior in the presence of capital market pressure and find that, in the presence of strong capital market pressure, managers behave more myopically when more frequent disclosure is provided. We then verify if the same pattern of results holds in a setting in which feedback is not mandatory, provided for internal purposes, and in which there is no capital market pressure. Second, previous literature investigating how feedback frequency affect individual decision making does not disentangle its effect on intertemporal choices from the effect of reward timing (Bellemare, Krause, Kröger, & Zhang, 2005; Gneezy & Potters, 1997). We disentangle these two components and offer empirical evidence on
The study of open quantum systems through quantum trajectories [1, 2] has helped to elucidate the potential of quantum feedback . This is particularly important for the measurement of conditional intensities in quantum optical systems. Our recent work in optical cavity QED uses such measurements to demonstrate the generation of ground state coherences by spontaneous emission [4, 5]. Coherences arise from the internal structure of the rubidium atoms and its response to small magnetic fields. Superpositions of ground state magnetic sublevels Larmor precess and reveal their Zeeman shift in the frequency of a quantum beat.
The rest of the paper is organized as follows. In Sect. 2, the model and mathematical preliminaries are introduced. The existence and asymptotic stability of the positive peri- odic solutions are proved in Sect. 3. A feedbackcontrol scheme is proposed in Sect. 4. An example and some numerical simulations are provided to verify the theoretical results in Sect. 5. Finally, a brief conclusion is given in Sect. 6.
tance to real life problems. For instance, under some conditions any solution of our main model (.) will jump into a positive invariant set and then stabilize with an order or or- der limit cycle or become free from impulsive eﬀects. At this stage, the system becomes inert with respect to further impulsive eﬀects and so, in theory, the control purposes can be successfully achieved by a sequence of one, two or a few impulsive actions or, alter- natively, by periodic interventions. Note that the analytical formula for the period can be calculated based on the initial values by employing the same methods as those used in . Although it is reasonable to assume that the carrying capacity of the pest population could be inﬁnity due to the threshold level considered in the model being quite small com- pared with the carrying capacity, the disadvantages of this work are: (i) the Lambert W function and its properties are needed for deﬁning the Poincaré map; and (ii) the ﬁrst integral of the ODE model plays a key role in most of the results. Therefore, if the carry- ing capacity is a constant rather than +∞, then the ﬁrst integral of the generalized model does not exist any more, and consequently the Lambert W function cannot be used. Thus, the question is how to extend all analytical techniques developed in this paper to investi- gate more generalized models with state-dependent feedbackcontrol. For our near future work, we will focus on model (.) with a constant carrying capacity and diﬀerent releasing strategies and other models arising from diﬀerent application ﬁelds.
DOI: 10.4236/ijcns.2019.127008 100 Int. J. Communications, Network and System Sciences There are many studies which focus on remote roboot systems with force feedback  . In , the authors asssess the Quality of Experience (QoE)  about the operability of a haptic interface device for work in which a user operates an industrial robot with a force sensor at a remote location by using the haptic interface device while watching video. They investigate the influence of network delay on the operability and the effect of the adaptive reaction force control . As a result, the control is effective for the remote robot system with force feedback. In , Banthia et al . make a prototype telerobotic system for live transmission line maintenance. In the system, a user can operate a haptic interface device at a local terminal to control a remote robot arm. Then, the user tries to do the maintenance by controlling the remote robot arm. They also invetigate the difference in force feedbackcontrol (unilateral or bilateral control) by experiment. However, in the papers, they do not carry out stabilization control for the remote robot systems with force feedback. On the otherhand, Miyoshi et al . propose stabilization control which uses the wave filter together with the phase control filter for a haptic telecontrol system in which 1-DoF haptic interface devices are employed in  and .
In this paper, an adaptive feedback controller is proposed to achieve the fi- nite-time stability of dynamical system. In the proposed scheme, the feedback gain of the adaptive feedback controller is automatically tuned according to the adaptation law in order to stabilize unstable fixed points of the system. Based on the Lyapunov function method and the finite-time stability theory, we get a sufficient condition for the finite-time stability. Finally, simulation results show the effectiveness and feasibility of the proposed finite-time con- troller.
In the last version (RobinHand L), the griping part which the operator holds in the hand during the manipulation of the motion controller has been improved. Now it is possible to perform the 7 degrees of freedom (7DOF). The degrees of freedom (ABC) that are used to control the tool/robot with additional articulated parts and the degree of freedom D that performs the opening and closing of the jaws of the instrument are carried out by the gripping part of the motion controller. The ergonomics of the gripping part have also been improved. Currently, it is adjusted to the operator's hands. The lines passing through the centres of the articulation elements intersect at exactly one point, between the operator's fingers. The force feedback is performed in the directions X, Y, and Z and in the jaw clamp D. Thanks to this solution, the manipulation of the motion controller became more intuitive. The construction of such complex shapes required the use of the latest technologies, manufacturing - 3D printing, as well as the connection of individual components (metal-plastic, metal-composite). Thanks to the use of rapid prototyping technology (3D printing with FDM method, used material: PCABS), it was possible to minimize the mass of the subassembly that was manipulated by the operator. This solution also allowed a shorter time for implementation of subsequent prototype versions. The minimum value of the force exerted on the user/surgeon was determined by using a test stand with one degree of freedom (Fig. 4).
To track a periodic signal and to eliminate periodic disturbance in dynamic systemsthe repetitive controller is widely used. In the repetitive control scheme, the present control input is obtained, and this operation is performed repetitively. Hence, the repetitive controller generates the control input that ensures zero tracking error . In the repetitive control scheme, a low-pass filter is used to disable the learning at high-frequency so that it allows tracking/rejecting periodic signals within a specified frequency range.
Traffic load is highly dependent on parameters such as time, day, season, weather and unpredictable situations such as accidents, special events or construction activities. If these parameters are not taken into account, the traffic controlsystem will create bottlenecks and delays. A traffic controlsystem that solves these problems by continuously sensing and monitoring traffic conditions and adjusting the timing of traffic lights according to the actual traffic load is called an intelligent traffic controlsystem.