Abstract: The usage of remote signal obtained from a wide-area measurement **system** (WAMS) introduces **time** delays to a wide-area damping controller (WADC), which would degrade **system** damping and even cause **system** instability. The **time** **delay** margin is defined as the maximum **time** **delay** under which a **closed**-**loop** **system** can retain stable. In this paper, the **delay** margin is introduced as an additional performance index for the synthesis of classical WADCs for flexible AC transmission systems (FACTS) devices to damp inter-area oscillations. The proposed approach includes three parts: a geometric measure approach for selecting **feedback** remote signals, a residue method for designing phase compensation parameters, and a Lyapunov stability criterion and linear matrix inequalities (LMI) for calculating the **delay** margin and determining the gain of the WADC based on a trade-off between damping performance and **delay** margin. Three case studies are undertaken based on a four-machine two-area power **system** for demonstrating the design principle of the proposed approach, a New England 10-machine 39-bus power **system** and a 16-machine 68-bus power **system** for verifying the feasibility on larger and more complex power systems. The simulation results verify the effectiveness of the proposed approach on providing a balance between the **delay** margin and the damping performance.

Show more
24 Read more

factorization is provided and leads to less conservative conclusions than solving a square root. The **time**-varying **delay** is assumed to belong to an interval and the derivative of the interval **time**- varying **delay** is not a restriction , which allows a fast **time**-varying **delay**; also its applicability is broad. Based on the Lyapunov-Ktasovskii approach, a **delay**-dependent criterion for the existence of a state **feedback** controller, which guarantees the **closed**-**loop** **system** stability, the upper bound of cost function, and disturbance attenuation lever for all admissible uncertainties as well as out perturbation, is proposed in terms of linear matrix inequalities LMIs. The criterion is derived by free weighting matrices that can reduce the conservatism. The eﬀectiveness has been verified in a number example and the compute results are presented to validate the proposed design method. Copyright q 2009 M. Xiao and Z. Shi. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Show more
16 Read more

characterizes the overall behaviour of the **closed**-**loop** **system**, indicating that it became slower in responding to the reference input. However, it does not provide insight into the behaviour of the individual components within the **loop** (e.g., eventual **time** delays in the human operator response). This **delay** increase cannot be ex- plained by the transition from a more continuous (100/ 100) to a discrete control (5/5). During this process the sampling **time** was increased from 0.01 to 0.2 s and this increase was too small to explain the delays of up to ap- proximately 1 s in the condition 5/5 [36]. Instead, we as- sume that this was likely the consequence of a poor perception of electrotactile stimulation at the low stimu- lation frequencies, compromising the subjects’ ability to interpret the **feedback** and react timely with an appropri- ate control action. Due to a poor perception, the **time** needed for the cognitive processing of the **feedback** in- formation might have increased or the subject changed the response strategy (e.g., acting more conservatively) due to higher uncertainty. A different analysis is neces- sary to obtain insights into these mechanisms, i.e., the methods for the identification of the systems in **closed**- **loop** [37,38], which is an important step, but outside the scope of the current study.

Show more
16 Read more

Once your simulated **system** has a reasonable response, and probably more importantly, reason- able gains, try running the ECP **system** with these gains. If the gains are not too large and the **system** works, save the results to a file. If the **system** buzzes and doesn’t work, go back to step 1 and try again.

As shown in the fig.2, the linear model consists of a gain unit, a limited integrator and a **delay** unit. The gain unit represents the **system** gain which determines the stability of the **system** and the limited integrator operates on the signal to limit the **system** steady state error. Ziegler-Nichols open **loop** tuning algorithm has been used in tuning the compensator. In this algorithm, controller settings are based on a second-order model with a **time** **delay** that approximates the **system** parameters. This method uses the Chien-Hrones-Resnick (CHR) setting with 20% overshoot. The Zeigler Nichols Open-**Loop** Tuning Method is a way of relating the process parameters **delay** **time**, process gain and **time** constant to the controller parameters, controller gain and reset **time**. It has been developed for second-order-lag processes followed by **delay** [4]. The transfer function of the desired **system** to be optimized is given by:

Show more
This paper is concerned with the problem of designing discrete-**time** control systems with **closed**-**loop** eigenvalues in a prescribed region of stability. First, we obtain a state **feedback** matrix which assigns all the eigenvalues to zero, and then by elementary similarity operations we find a state **feedback** which assigns the eigenvalues inside a circle with center and radius. This new algorithm can also be used for the placement of **closed**-**loop** eigenvalues in a specified disc in z-plane for discrete-**time** linear systems. Some illustrative examples are presented to show the advantages of this new technique.

Show more
Dynamic **feedback** based **closed**-**loop** medical devices offer a number of advantages for treatment of heterogeneous neurological conditions. **Closed**-**loop** devices integrate a level of neurobiological **feedback**, which allows for real-**time** adjustments to be made with the overarching aim of improving treatment efficacy and minimizing risks for adverse events. One target which has not been extensively explored as a potential **feedback** component in **closed**-**loop** therapies is mitochondrial function. Several neurodegenerative and psychiatric disorders including Parkinson ’ s disease, Major Depressive disorder and Bipolar disorder have been linked to perturbations in the mitochondrial respiratory chain. This paper investigates the potential to monitor this mitochondrial function as a method of **feedback** for **closed**-**loop** neuromodulation treatments. A generic model of the **closed**-**loop** treatment is developed to describe the high-level functions of any **system** designed to control neural function based on mitochondrial response to stimulation, simplifying comparison and future meta-analysis. This model has four key functional components including: a sensor, signal manipulator, controller and effector. Each of these components are described and several potential technologies for each are investigated. While some of these candidate technologies are quite mature, there are still technological gaps remaining. The field of **closed**-**loop** medical devices is rapidly evolving, and whilst there is a lot of interest in this area, widespread adoption has not yet been achieved due to several remaining technological hurdles. However, the significant therapeutic benefits offered by this technology mean that this will be an active area for research for years to come.

Show more
18 Read more

where (1 6,10,10) Q diag e = , R = 1 , and N = 0 , for the augmented plant description with the integrator on the error signal, where the states are defined as x = { e i , , ω } T . Q, R, and N are determined experimentally by finding the LQR gain whose performance best mirrors that of the PI controller during a non-**delay** case trial. This puts the largest penalty on the error while also keeping the control values within the acceptable limits of ± 12V . The white noises v t ( ) and w t ( ) are assumed to be zero in order to properly compare the performance of each methodology. The assumption is that the network **delay** is the dominating factor of the **system** performance and stability.

Show more
98 Read more

Direct current (DC) motor has already become an important drive configuration for many applications across a wide range of powers and speeds. The ease of control and excellent performance of the DC motors will ensure that the number of applications using them will continue grow in future. This paper is mainly concerned on DC motor speed control **system** by using microcontroller PIC 16F877A. It is a **closed**-**loop** control **system**, where optical encoder (built in this project) is coupled to the motor shaft to provide the **feedback** speed signal to controller. Pulse Width Modulation (PWM) technique is used where its signal is generated in microcontroller. The PWM signal will send to motor driver to vary the voltage supply to motor to maintain at constant speed. Through this paper, it can be concluded that microcontroller PIC 16F877A can control motor speed at desired speed although there is a variation of load.

Show more
Problems connected with feedback (closed-loop) stability, controller limitations and dead-time compensation to obtain minimum variance (mean square) control at the output are[r]

14 Read more

Abstract—This paper presents a new method of controlling the speed of PMDC motor with the auto tuning of parameters of the PID controller in the on-line speed control and also extracting the model of the **closed** **loop** **system** through LabVIEW. PID controllers provide robust and reliable performance for most systems if the PID parameters are tuned properly. This objective is achieved by using an auto tuning PID in three steps. In the first step, the PMDC motor-generator set is interfaced to Laptop using NI USB-6008 DAQ card. In the second step, the **closed** **loop** **system** is extracted through the LabVIEW **system** identification toolkit. In the third step, the PID parameters are obtained through the auto tuning procedure and speed controlling is done. The designed auto tuning PID controller realize a good dynamic behaviour of the DC motor, a perfect speed tracking with less rise and settling **time**, minimum overshoot, minimum steady state error and give better performance compared to the manual tuning PID controller.

Show more
• Thus, in state space, given the pair (A,B), we can always determine the K (gain), to place all the **system** **closed**-**loop** poles in the left-half of the plane if and only if the **system** is controllable – that is, if and only if the controllability matrix C M is of full rank.

16 Read more

LQR controller has been designed for the AFTI/F16 aircraft based on linearization of the state space model. The performance specifications achieved indicate that the **system** settles at a much faster rate using the proposed advanced linear control method rather than the conventional Pole Placement method. The overshoot obtained for a step input is found to be very minimal being a very critical requirement for the fighter aircraft. The output pitch angle tracks the desired reference input at steady state. The LQR technique attains the desired performance specifications achieving **closed** **loop** stability without increasing the order of the **system**. Comparative study has been carried out with the results obtained from Pole Placement technique. Simulation results validate that using LQR technique, an improved transient response specification has been achieved, the step response of the **system** with LQR settles at a much faster rate giving less overshoot compared to Pole Placement technique.

Show more
Though there are many solution algorithms, there are fewer references on perturbation analysis of the pole-assignment problem [14]. A perturbation analysis for the single-input case is given in [2]. Perturbation analyses for both single-input and multi-input cases are given in [14], under the assumption that the **closed**-**loop** **system** has no repeated eigenvalues. With the same assumption, perturbation theory for the single-input case is developed in [11]. Note that for the single input case, A − BK is diagonalizable if and only if its eigenvalues are distinct [10]. Characterization of the set of ill-posed problems (A, B), under the assumption that there is no intersection between the set of eigenvalues of A and that of A − BK, is considered in [5]. A perturbation analysis for multiple input pole placement can be found in [12], where perturbation results for the **feedback** gain and the poles of the **closed** **loop** **system** are provided, along with computational results comparing the actual poles with the eigenvalues of the **closed** **loop** **system** formed from (A, B) and the perturbed gain matrix.

Show more
18 Read more

e) Implement (Simulink/Matlab) a state observer with state variable **feedback** configuration that forces the **system** to be a type one **system** for the one degree of freedom **system** with the state model on the web. Utilize an lqr controller, the last Q penalty value is a penalty on the new (augmented) state. Use the command k = lqr([0.1 0 1], 10). To determine the **closed** **loop** poles type p = eig(A-B*K). Set the observer poles equal to 2.5 times the state **feedback** poles (2.5*p). Set all initial states (observer, plant, and augmented state) to zero You should get results similar to those displayed in Figure 3. Turn in your plot and Matlab/Simulink code.

Show more
This paper presented the development of a robotic wrist orthosis for joint rehabilitation. Mechanical development of the orthosis and a preceding prototype was demonstrated. The primary task was to develop a control **system** for the utilised pneumatic actuators. As a majority of existing robots for wrist rehabilitation are applying rigid actuators, this work presents an exploratory implementation of soft wrist orthosis. To control such a PAMs-driven robot in high-performance, a model-based controller that relies on a predefined static model of the actuator was developed. The model-based controller resulted in a look-up table that characterises the relations between force and displacement parameters and the pressure within the actuator. In order to guarantee the trajectory accuracy as well the force safety, an embedded **closed**-**loop** pressure control **system** was implemented, in order to set the pressure in each muscle according to the desired displacement and torque. The safely trajectory planning method was used in this **system** to test its performance. The resulting angle curve as well as their parallel force measurements were presented. In the end, the utilised control method allowed the trajectory following with a mean squared error of 6°. The dynamic torque measurement was interfered by friction in the mechanical parts of the device, leaving the device with a measured maximum torque of about 0.1Nm during the trajectory period.

Show more
We proposed a delta-sigma architecture with **feedback** **loop** which gives a novel linear transfer function be- tween the gas concentration and the infrared signal intensity. The **feedback** **loop** is built based on the received intensity of infrared sensor during the heating cycle. Once the received signal intensity rises across a pre-set threshold level, the output of a comparator will change from low to high. The output signal is delivered to an ARM based microprocessor which controls a Power-PMOS and the switch on and off is decided by our pro- posed Delta-Sigma algorithm. The proposed algorithm gives a ratio value of heating numbers and total sampling numbers which shows a linear relationship with the gas concentration.

Show more
ABSTRACT: A controller designed specifically for a nominal process model often works well for the nominal plant model, but may fail even by a little change in it. Robust control deals with analysis and controller design for such imperfect **system** with bounded modelling errors. A lot of research has been done and many methods are available for robust design of the plants. In this paper, a graphical technique is followed to find all PID controller gains that satisfy the robust stability constraint of a given DC motor model with **time** **delay** .

Copyright © 2018 Fucheng Liao et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. A finite-**time** bounded tracking control problem for a class of linear discrete-**time** systems subject to disturbances is investigated. Firstly, by applying a difference method to constructing the error **system**, the problem is transformed into a finite-**time** boundedness problem of the output vector of the error **system**. In fact, this is a finite-**time** boundedness problem with respect to the partial variables. Secondly, based on the partial stability theory and the research methods of finite-**time** boundedness problem, a state **feedback** controller formulated in form of linear matrix inequality is proposed. Based on this, a finite-**time** bounded tracking controller of the original **system** is obtained. Finally, a numerical example is presented to illustrate the effectiveness of the controller.

Show more
12 Read more

systems is proposed in terms of linear inequalities. Based on this, conditions for the existence of robust state-**feedback** controllers are established. Moreover, the total number of all the nonzero elements of the controller gain is to be minimized, while satisfying a guaranteed level of L 1 -induced performance. Then,