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It is universally acknowledged that identifying the best control system along with its form factor are some of the decisions that an individual has to make when it comes to defining the best active isolation for an organization (Liu & Li, 2012). Additionally, most sensors that are established are in a position to detect parameters such as velocity, displacement, and acceleration. In this case, the systems that use these aspects are known to employ a combination of active isolation and active isolation technologies. As such, there are two accepted ways or rather control systems that are used to describe elements that revolve around active isolation systems, as well as feed-forward and feedback control systems (Zhang & Wang, 2014). In this case, a feedback control system is proven to continuously evaluate, examine, and monitor the platform used in modifying and controlling its output based on the retrieval of the data that vibrated. In essence, when it comes to feedback controlling system, it is accepted that the disturbances caused by the environment or experiments that cause vibration are determined or rather measured and the feedback is sent back to help curb the implication of the disturbance (Zhang & Wang, 2014). In turn, a feed-forward control system is known as an anticipative form of control system in the sense that the control system responds in a reactive or rather predefined manner when dealing with vibrations caused by disturbances. In simple terms, this type of controlling system is employed in cases where the measured disturbance is predetermined or is well understood. However, based on scientific findings, it is proven that the two controlling systems work best when they are incorporated into the same system (Liu & Li, 2012). Therefore, to understand the concept of mechanical vibration and controlling systems, it is necessary to explore the concepts of feedback control and feed-forward control systems taking into consideration some of the advantages and disadvantages of each controlling system.

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Question 1: Feed-Forward Control

Feed-forward is a term that is used to explain a pathway or an element that exists within a control system and passes a signal that serves controlling purposes from a source externally. In most cases, this signal emanates from an external operator to material that can be acknowledged elsewhere as a load and exists in its external environment (Zhang & Wang, 2014). Additionally, it is known that a control system that operates based on the feed-forward behavior deals with implications of its control system in a manner that is predetermined without necessarily reacting to how its load responds (Liu & Li, 2012). In simple terms, it reacts directly opposite to the controlling system that possesses feedback, which depends on the adjustment of its output in dealing with how the load reacts and, in the process, dealing with how the characteristics of the load may alter unpredictably since it is classified as a part of the system that is categorized among the external environment.

One primary attribute of the feed-forward system revolves around the fact that the adjustment of its control variable is not error-based. However, its adjustment depends on knowledge and awareness about the mathematical model process coupled with knowledge regarding measurements of disturbances of the mathematical model (Liu & Li, 2012). It is for this reason that elements are required to make the control scheme dependable through the employment of pure feed-forward. In this case, there is no feedback. In such instances, the controlling or external environment must be present and implications of the controlling system in question and its effect on the load should be established (Zhang & Wang, 2014). In other words, the load must remain unchanged predictably within a given time frame. Sometimes, this kind of feed-forward control is acknowledged as ballistic since, once initiated, it cannot be modified further; hence, any adjustment that needs to be made will be corrected by a new control signal. image1.jpg

Overview and How Feedback Control Can Be Used In the Process of Controlling Applications

It is acknowledged that when it comes to feed-forward control, all the adjustments or rather disturbances are determined and taken into consideration before they get a chance of impacting the controlling system. For instance, in the house this kind of the controlling system may establish the fact that the house door has been left open, in the process alerting the heater before the house is filled with cold. However, the challenge that individuals can incur with feed-forward control system revolves around the fact that the implication of modifications or rather the disturbances on the mathematical model must be predicted accurately (Zhang & Wang, 2014). As such, cases of unmeasured disturbances must not be witnessed. For example, in the case of a house if a parameter of the house, for instance, a window left open, is not a disturbance that is being measured, the thermostat might still react to the situation and let the house cool down as indicated in figure 2 below.

Combined feed-forward coupled with feedback control is universally acknowledged as a system that can improve performance levels of a control system as compared to the simple feedback control, especially given cases where measured disturbance is needed to be determined before impacting the output. In other words, in an ideal situation it can be argued that feed-forward system can remove the implications of the measured disturbance that is embedded in the process output (Zhang & Wang, 2014). As such, whenever there are errors in regards to modeling, this type of control can eliminate the implication of measured disturbance on the system output levels better as compared to other system controls, especially the simple feedback control model. Nevertheless, the decision as to whether to employ the feed-forward control is guided by the fact that the improvement level, as far as the adjustment of the disturbance is concerned, justifies the maintenance and implementation cost (Zhang & Wang, 2014). In simple terms, economic benefits attached to the feed-forward control can result from increased salability or lower operating costs because of its consistent quality. This kind of controlling system is always preferred when collaborating with feedback control since the feedback control in this case is needed to help in tracking set point changes, while helping in suppressing undetermined disturbances that are always present, but some control systems cannot notice them in any real process.

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Modeling Process (Calculation of Feed-Forward Rotational Speed)

The inertia of a load can be calculated or determined. In this case, it is universally acknowledged that the torque that is needed to increase the speed of inertia is equal to the sum of acceleration rate and the inertia itself (Liu & Li, 2012). In this case, if an individual is able to make an option of a frictionless system and the desired acceleration rate and the inertia are established, the torque needed to make the inertia accelerate to a given level of acceleration can be calculated easily (Zhang & Wang, 2014). As such, it is possible to comprehend that the derivative speed represents acceleration. In simple terms, the derivative attached to the clean speed reference will produce the rate of acceleration. In the process, the speed reference achieved can be multiplied by the inertia force known to produce the required torque to increase the inertia in such a way that the speed of rotation is able to track the reference speed in the name of inertia compensation. As a result, the system will be able to track the reference speed without closing the speed loop and it is classified as an open loop controller since it operates on the calculated feed-forward torque reference (Liu & Li, 2012).

Applicability of Feed-Forward Control

As opposed to the feedback control, this type of control takes action immediately; a disturbance is realized in the system without having to wait for a process variable deviation. In so doing, the feed-forward control is able to directly and quickly cancel the implications of disturbance. To achieve this, it is argued that it produces its action of control depending on the determined level of the measured disturbance. When it is employed in a controlling system, it is almost implemented as another system of feedback control (Zhang & Wang, 2014). In such a case, the function of the feedback controller is to tackle major disturbances, hence leaving the feed-forward controller to deal with the remaining factor that may result in the process variable moving away from its established point. For instance, when feed-forward control is employed in the heat exchanger, which is known for causing major disturbances in the flow rate of the entire process, the feed-forward control can be employed in adjusting the flow rate of the steam proportionally and this is achieved by the automatic functioning of the feed-forward controller (Liu & Li, 2012). image3.jpg

Question 2: Comparing Relative Merits and Demerits of Feed-Forward and Feedback Configurations

Feed forward and feedback control systems are universally acknowledged as the two types of control schemes for those application systems that respond to the changing dynamics of the environment automatically (Liu & Li, 2012). Additionally, each system utilizes sensors in determining the most crucial factors and established principles to react to any modifications or configurations in those environmental factors (Zhang & Wang, 2014). In essence, feed-forward and feedback controls may be incorporated in the same system, but they work in a very different manner. Feedback control system determines values, while reacting to changes in the measured value. Judging by the example, a thermostat is able to determine ambient temperatures in the house and, if it happens that the temperature goes below the required level, the thermostat is activated automatically to increase the temperature to the required levels (Liu & Li, 2012). As such, it can be argued that as much as the thermostat determines the temperature, it also gives feedback to the system to maintain the temperature.

In turn, the feed-forward may be able to determine a number of variables in terms of secondary rather than primary variables. In this case, feed-forward thermostat may be in a position to determine internal and external temperatures simultaneously and it is also able to send signals in the process whenever doors are closed or opened.

Merits of feed-forward control and feedback control are embedded in instances such that, if the controlling system determines the temperature outside as being low and the window is opened, then the thermostat will react to the environment by preventing the house from cooling down because of the cold outside (Zhang & Wang, 2014). In other words, the system reacts automatically instead of waiting for the external temperature to impact the house temperature since it anticipates implications of the open window to counteract the impeding heat loss. In fact, a video car is another good example of a feed-forward controller since it is able to increase the speed of the fan because of the reaction to the intense graphics activity in a move meant to dissipate heat before the real temperature increases.

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Advantages

Feedback control systems are universally known as simple systems. In this case, the system is able to determine variables and in the process it employs the determined variable for making a decision (Liu & Li, 2012). Apparently, feed-forward systems have the capability of anticipating any modifications in the determined variable in such a way that they realize this function by working in a proactive manner instead of reacting to every factor. In other words, the more secondary factors the controlling system is able to detect and determine, the more accurately it is able to work.

Disadvantages

Feedback systems are at times known to be inaccurate. As such, a thermostat is known to perform its functions effectively in maintaining the temperature, but it is believed that in some instances ambient temperatures fluctuate to a certain level as the level of house furnace switches off and on as the reaction to the thermostat signals. Additionally, variables that are unexpected, such as a door or windows left open, can make it challenging for the feedback system to work effectively (Zhang & Wang, 2014). On the same level, the feed-forward system works best only based on the information that the system has detected to react to. In this case, it cannot take into consideration some of the undetermined variables when it comes to decision making and such challenges may result in a system breakdown. It is for this reason that so many controlling system designs are embedded with both feed-forward and feedback controlling systems to offer a back level when it comes to controlling the environment disturbances (Liu & Li, 2012).

Reason Why They Are Better Together

Feed-forward controlling system is able to anticipate the implication of the determined disturbance and in the process it deploys necessary actions that are able to deal with impeding implications of the disruption on time (Liu & Li, 2012). In so doing, it can improve rejection of disturbances in performance, but this is only meant to deal with the disturbance in question. Additionally, by incorporating the two controlling systems together, a solution for improved rejection to any impeding disturbance variables, even if it is not basically a variable embedded in a secondary process, can be established. Moreover, it is also argued that the feed-forward system is only important if an individual’s concern is concentrated on one specific variable disturbance that has been acknowledged to result in repeated disturbance of the ongoing process. However, to improve on this benefit performance, it is acknowledged that the feedback system must be incorporated together with the feed-forward to ensure that additional disturbances are determined and reveal process disturbances to help the system have ample time for computing and establishing preemptive control reactions (Zhang & Wang, 2014).

Question 3: Determine the Feed-Forward Control and Implementing Process

Most PID controllers possess eternal links for adding an input that is obtained from a feed-forward system controller. In this case, the output derived from this system can otherwise be externally added to the feedback controller’s output (Liu & Li, 2012). As a result, it is important to review documentation of the controller and take special care when it comes to scaling the feed-forward signal. Under normal circumstances, feed-forward controllers are demarcated between -100% and +100%. In essence, it is recommended that the feed-forward control be implemented together with the cascade control to ensure that their actions are able to linearly manipulate their physical process and in the process remove the control valve mechanical problems and nonlinearity (Liu & Li, 2012).

Designing Feed-Forward Controller without Feedback Controller

In this case, it is assumed that the process variable has an identifiable intermediate variable. In the design model, the process will have three inputs such that one output will be the measured disturbance that is wished to be controlled and the other two will be the disturbances. In this case, transfer functions Gd1 (s), Gd2(s), and Dm(s) may represent the same equipment assembly, but in the process they specify how variable y, which is the output variable, relies on each control input (Liu & Li, 2012). Taking the above elements into consideration, the Laplace process definition formula will be: y(s)=GmXm(s)+Gd2Xd2(s)+Gd1Xd1(s).

As such, a case in which Gm(s) could be divided into two parts is imagined connected by a determined or rather measurable intermediate variable Xi. In this case, this can be associated with the simple model of two tanks in series (Zhang & Wang, 2014). After the establishment of the interior structure of Gm, it is important to take into consideration Xd2 as the upstream disturbance and Sd1 as the downstream disturbance immediately after the intermediate variable.

The formula in this case becomes: y(s)=Gm2Gm1Xm(s)+Gd2aGm1Xd2(s)+Gd1Xd1(s).

Bringing the two equations together, Gm=Gm2Gm1.

In this equation, the objective is to control the variable y, which is the known disturbance at a set point. In this case, it is important to assign variables in the overall dynamic process since the equation variable is y (Isermann, 2013). In other words, the manipulated variable implications react to the consequences of the controlled variable via the transfer function. In case the set point deviates from the established measurable disturbance, a control action may not be noticeable since there is no feedback control that can quickly send the message back to the input for further processing.

Design with Feedback Control

When it comes to feedback control implementation, it is acknowledged that it requires very little or no mathematical knowledge of the process to be controlled (Isermann, 2013). As much as a mathematical model is not needed, it can at times be crucial for the control system design. Additionally, a process that involves a feed-forward controller designed together with a feedback controller is both versatile and robust in the sense that if the process conditions are modified or configured, returning the controller offers satisfactory control (Zhang & Wang, 2014). Since there is only one known measurable disturbance, it can be argued that since most disturbance variables that are associated with feedback control must be determined online, this is not feasible in a real-life situation.

If a number of disturbances exist, a feed-forward controller can be established for each of them. However, in this design model the control system is being established for a measured disturbance. However, outputs that are realized from the entire feed-forward controller can be simulated together to offer one final signal of feed-forward (Isermann, 2013). Therefore, in the modeling of the feed-forward system, it is important for an individual to take into consideration the following disturbance criteria:

· Disturbances occur rapidly in such a way that the feedback control cannot react immediately they happen;

· Disturbances possess predictable implications on the process and are based on experimental results. Most disturbances fall into this group;

· Disturbances are measurable since if they are not measurable, it is difficult to control them (Isermann, 2013).

Question 4: Ratio Control and Its Importance for the Control Process

Ratio control can be defined as a feed-forward control that is special in nature in the sense that it has a widespread application when it comes to process industry (Isermann, 2013). In this case, the main goal consists in keeping the ratio of two process variables as a value that is specified. In this case, the two variables in question are in most cases flow rates, including a disturbance variable d and a manipulate variable u. Hence, the ratio can be said to be controlled as opposed to the individual variables in question. In the equation below, d and u are classified as physical variables, hence making them uncontrollable and not deviation variables (Liu & Li, 2012).

R= u/d

However, regardless of the manner in which the ratio control is established, it is argued that the variables applied in the process must be scaled in the most appropriate manner.

Examples of typical applications of ratio control revolve around:

· maintaining a stoichiometric ratio when it comes to reactants to a reactor;

· maintaining a specified distillation column’s reflux ratio; and

· setting relative amounts of components required in operations that revolve around blending.

When two flows come together, the ratio control serves the purpose of manipulating the other flow in an effort to keep the desired proportional ratio between the two flows. In this case, what is manipulated by the ratio flow is what is sometimes referred to in the process flow as the controlled flow. In case an individual wants to treat water using chlorine, it can be argued that the chlorine is the controlled flow, while water is the wild flow; in this case, it is established based on an external objective (Isermann, 2013).

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Conclusion

To understand the concept of mechanical vibration and controlling systems, it is best to explore the concepts of feedback control and feed-forward control systems taking into consideration some of the advantages and disadvantages of each controlling system. Additionally, it is known that a control system that operates based on the feed-forward behavior deals with implications of its control system in a manner that is predetermined without necessarily reacting to how its load responds. In this case, feed-forward control loops are known to be applied in attenuation of onboard vibrations such that the measured disturbance is already established. In turn, the feedback control system is known. Feedback control system determines values, while reacting to changes in the measured value. Hence, it can be concluded that the two systems may produce better results if the feed-forward control is incorporated into the feedback control model.

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