Fuzzy Logic-Based Control of Manufacturing Processes Term Paper

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Fuzzy Logic-Based Control of Manufacturing Processes

Enormous advances in technology have made everyday life much easier. New developments within control systems have allowed for greater empowerment for individual devices, which often takes the burden off of the user. Among the many new technologies based on artificial intelligence, Fuzzy Logic Control System is the most popular and most applicable system. Almost in all domains, Fuzzy logic has a broad application area. It is safe to say that we can replace all control-based systems by Fuzzy Logic Control System. FCLS can be used in a great variety of commercial and industrial applications, showing its strength and prominence as a new technology prompt for future innovation.

Fuzzy Logic is a principle within artificial intelligence that is based primarily off the notion of logical reasoning that humans use daily in the context of the normal everyday lives. There are a number of instances where the value of stimulus and external information cannot compute to directly absolute true or false connotations. Rather, there is a middle ground that is ambiguous in nature. This ambiguity can also be seen as the fuzzy area, where individuals have to use intuitive decisions and critical thinking to apply commonsense notions to situations that do not prompt absolute notions of true or false [8]. Working within the fuzzy area helps empower individuals to make decisions and act in certain ways without having to require the absolute nature of a true or false decision. This type of reasoning can be translated into artificial intelligence, which would thus empower machine systems to make the same commonsense decisions within situations that are not in absolute sure false connotations. This is a human rationalization that has traditionally been left out of automated machine processing. Yet, in today's advances in technology, "fuzzy control theory is designed to replicate human reasoning, thinking and response mechanisms" in a way that can greater empower artificial intelligence to think more freely like a human [5].

Thus, fuzzy logic essentially allows control systems to work within that gray ambiguous area without breaking down or proving incapable of moving forward. When control software uses fuzzy logic principles, it operates at a much more fluid and flexible design. According to Dewy, it is able to make decisions on a number of flexible "if-then rules" [3]. When this situation occurs that has no absolute true or false value, the control software is not stuck in indecision. Fuzzy logic programming allows the system to make decisions within the ambiguous gray area. In the figure below, the gray shaded area are all the values that are absolutely true "beyond a shadow of a doubt," while the crosshatched area represents values that are absolutely false [3]. If all values are either absolutely true or absolute false, the system does not need the increased critical thinking capabilities present within fuzzy logic [1]. Yet, this is not always the case. In the middle, is ambiguous region that is neither absolutely true nor false. Fuzzy logic comes into play when there are values that rest within this ambiguous region. In most application processes, there are some values of data that lie within the common area, between true and false. As Dewy suggests, "information which lies within the common area has to be studied, stored, and used to quantify and to classify the data," which "allows for smart manipulation of the data structure in order to make inference to a solution" [3]. Essentially, fuzzy logic allows control systems to make educated decisions for data that falls within this common area, as based on its capability to study and quantify such data on more complicated categorical structures. Ultimately, this allows control systems to make smarter decisions without the constant need for interruption by a human controller [8]. There may be no need if it is an easy control system which means if it works well with PID control system. But for more complicated control systems, Fuzzy Logic Control System can be the best way to use.

Additionally, fuzzy logic systems can help streamline control system processes. In many situations, the input signal into a control system can be quite complex, or "noisy" [8]. There is simply too much information streaming into the control process, which ultimately clogs up its ability to input incoming data. Unfortunately, this noise "tends to corrupt the integrity of the actual signal," and can cause serious problems in processing incoming data [2]. Fuzzy logic control systems can help quiet some of that noise.

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In such a system, fuzzy logic empowers the control system to use common sense capabilities to funnel out noisy data that is not needed in the actual input. The system can study and judge incoming data in order to strengthen decision-making skills to help streamline the process of data input with less noise to corrupt the signal. Fuzzy logic allows the control system to make humanlike decisions to adapt the system to the most practical fit in order to most efficiently deal with the incoming data.

With the ease-of-use and increase reliability to handle complex situations, fuzzy logic works incredibly well within household retail applications. Its ability to help make decisions without constant supervision empowers commercial devices to work with little interruption from the consumer which purchase them. Devices with the Fuzzy Module embedded within them takes away some of the burden on the consumer to have to constantly deal with control processes in the device. Rather, fuzzy logic allows the device to think for itself, creating greater ease-of-use for the consumer. A number of devices currently implement such control systems, including "camcorders with automatic compensation for operator injected noise such as shaking and moving; elevators with decreased wait time, making intelligent floor decisions and minimizing travel and power consumption; antilock braking systems with quick reacting independent wheel decisions based on current and acquired knowledge; television with automatic color, brightness, and acoustic control based on signal and environmental conditions," [3]. Clearly, there are a number of commercial devices that already implement this type of control system. Any type of electronic or consumer device that needs to make some sort of decision-making on its own uses the principles of fuzzy logic. This helps take away the need for the consumer to be a master in working the device, because the devices in power to make its own commonsense base decisions to adapt to changing environments.

As such, FLCS finds a big chance in commercial appliances, especially in heat control and climate systems. The ability to add greater intelligence to thermostats helps monitor them. Home, car, and industrial AC and heating systems are now regulated primarily by fuzzy logic control mechanisms [2]. According to the research, car and home AC systems use fuzzy logic to better estimate temperatures and thus decide on a course of action based on those temperature readings [1]. The fuzzy logic controllers within the thermostats help adjust for changing temperatures and conditions throughout the day without the need for human intervention. It helps allow for greater consistency that increases the comfort within homes and office buildings without the constant demand of human supervision of the thermostat device. Fuzzy logic empowers thermostats to become "an intelligent thermostat that understands both different environmental conditions in the current needs of the user" [1]. This makes systems much easier to use, but also much more efficient. Moreover, FLCS help reduce unneeded energy waste, by better regulating AC and heating control functions [6]. Heating and cooling systems of residences and commercial office buildings take up enormous amounts of energy. By using fuzzy logic, new innovators in technology have generated more eco-friendly energy-saving technologies for the control of climate systems. Fuzzy logic helps empower thermostats and control mechanisms to better regulate for consistent level of temperature control without wasting energy. Less supervision and dependence on human control methods is needed, while the control systems are able to better regulate themselves more efficiently and thus save energy.

Today, FLCS is used to control the heating and cooling in these kinds of systems by fuzzy Logic thermostats. In most commercial applications today, fuzzy logic control mechanisms have replaced the traditional PID system for controlling device operation. The PID system is an inexpensive microprocessor that controls operations based on auto tone functions. It was often used in thermostats applications in order "to help determine the thermal characteristics of a particular system," where "the method of autotune is to make a step input into the final control element and monitor the output" [3]. This ultimately results in a proportional relationship established between input and output decisions, which helps maintain a certain degree of control over functioning. However, Fuzzy Logic systems offer a number of benefits that have increasingly prompted commercial manufacturers to deal with the heightened cost of its implementation over PID control systems. In PID controls, there is a constant need to adjust settings, like the ones found on common thermostats. FLCS allows for less demanding attention paid to the.....

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