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Introduction
Published in Hitay Özbay, Introduction to Feedback Control Theory, 2019
Examples of feedback are found in many disciplines such as engineering, biological sciences, business, and economy. In a feedback system there is a process (a cause-effect relation) whose operation depends on one or more variables (inputs) that cause changes in some other variables. If an input variable can be manipulated, it is said to be a control input, otherwise it is considered a disturbance (or noise) input. Some of the process variables are monitored; these are the outputs. The feedback controller gathers information about the process behavior by observing the outputs, and then it generates the new control inputs in trying to make the system behave as desired. Decisions taken by the controller are crucial; in some situations they may lead to a catastrophe instead of an improvement in the system behavior. This is the main reason that feedback controller design (i.e., determining the rules for automatic decisions taken by the feedback controller) is an important topic.
Basic Feedback Concept
Published in Bogdan M. Wilamowski, J. David Irwin, Control and Mechatronics, 2018
Tong Heng Lee, Kok Zuea Tang, Kok Kiong Tan
All physical control systems are subjected to some types of extraneous signals and noise during operation. These signals may cause the system to provide an inaccurate output. Examples of these signals are thermal noise voltage in electronic amplifiers and brush or commutator noise in electric motors. In process control, for instance, considering a room temperature control problem, external disturbance often occurs when the doors and windows in the room are opened or when the outside temperature changes. A good control system should be reasonably resilient under these circumstances. In many cases, feedback can reduce the effect of disturbance/noise on the system performance. To elaborate, consider again the open-loop and closed-loop systems of Figures 2.1 and 2.3, respectively, with a nonzero disturbance/noise component n, at the input of the plant G(s). Assume that both systems have been designed to yield a desired response in the absence of the disturbance/noise component, n. In the presence of the disturbance/noise, the change in the output for the open-loop system is given by Δy(s)=G(s)n(s)
Force-System Resultants and Equilibrium
Published in Richard C. Dorf, The Engineering Handbook, 2018
In many systems, there is feedback (positive or negative) from the output to the input. Negative feedback makes a system more stable, while positive feedback causes a system to become unstable and is the principle behind the operation of oscillators. Feedback is depicted in a block diagram through a feedback transfer function G(s) between the output and the input, as shown in Figure 100.2 Note that in this case, U(s) is the input, and the output X2(s) is fed back to the input through G(s). The input X1(s) to H(s) can be expressed as X1(s)=U(s)-X2(s)G(s)
Active vibration control of smart beam by μ -synthesis technology: modeling via finite element method based on FSDT
Published in Mechanics of Advanced Materials and Structures, 2023
Shubo Zhang, Ye He, Lei Fan, Xiaoan Chen
In active vibration control, piezoelectric plates have been widely used as sensors and actuator [27]. There are mainly two types of active vibration control: feedforward control and feedback control. Feedforward control needs the excitation signal of the structure, so vibration cannot be controlled by feedforward control. Feedback control can be classified into output feedback and state feedback. Methods of modern control design mainly includes: LQR and LQG (static state feedback) control [28], PID and PD control [6], VSC (sliding mode control) [29], control and control [30], MPC (model predictive control) [31], and -Synthesis (robust control) [32, 33], etc. In addition to active and passive vibration controls, a self-control method combining the passive damping capabilities with the active control properties was presented in [34].
Differentiation among bio- and augmented- feedback in technologically assisted rehabilitation
Published in Expert Review of Medical Devices, 2021
Giovanni Morone, Sheida Ghanbari Ghooshchy, Angela Palomba, Alessio Baricich, Andrea Santamato, Chiara Ciritella, Irene Ciancarelli, Franco Molteni, Francesca Gimigliano, Giovanni Iolascon, Pierluigi Zoccolotti, Stefano Paolucci, Marco Iosa
In general, we could say that feedback is the return of the outcome (or a portion of that) of a system to its input for modifying its next state. The system could be the human sensorimotor control as well as to a machine control. It could be in real time, if provided during the execution of movements to modify the next step of this execution, or given after the end of the movement to modify the next execution. Biofeedback, augmented feedback, and neurofeedback are three types of real-time feedback. Conversely, the feedback provided at the end of task execution can be called as performance feedback. It should be mentioned that human sensorimotor system works also using feedforward control, predicting the next state. These aspects are out of the scope of this review and they were well treated by Wolpert and colleagues [13,32,33].
Dynamic modelling and simulation of rail car suspension systems using classic controls
Published in Cogent Engineering, 2019
I. A. Daniyan, K. Mpofu, O. L. Daniyan, A. O. Adeodu
Figures 17 and 18 show the rejection of disturbances from output sources by the system. The PID controller was further tuned to reject disturbances in the form of external (outside the system dynamics) and internal (as a result of variations that characterize the linear system dynamics). The active disturbance rejection uses the nonlinear steady-state error to check the total disturbances (sum of external and internal disturbances). With the feedback mechanism, the controller is able to use the system’s output to fine tune the input of the system such that the effect of various disturbances within and outside the system was minimized. As such, the total sinusoidal disturbances within the system could not create any significant ride discomfort. From Figures 17 and 18, the downward slope of plot, which indicates the amplitude of oscillation with time for the external disturbances (above 1 m) and internal (10 m) was gradually reduced to zero after about 10 s using the disturbance rejection control. This indicates that the active control system was able to check unwanted vibrations and achieve good stability during the rail car operation.