1.5V fully programmable CMOS Membership Function Generator Circuit with proportional DC-voltage control

A Membership Function Generator Circuit (MFGC) with bias supply of 1.5 Volts and independent DC-voltage programmable functionalities is presented. The realization is based on a programmable differential current mirror and three compact voltage-to-current converters, allowing continuous and quasi-linear adjustment of the center position, height, width and slopes of the triangular/trapezoidal output waveforms. HSPICE simulation results of the proposed circuit using the parameters of a double-poly, three metal layers, 0.5 μm CMOS technology validate the functionality of the proposed architecture, which exhibits a maximum deviation of the linearity in the programmability of 7 %

A Novel Programmable CMOS Fuzzifiers Using Voltage-to-Current Converter Circuit

This paper presents a new voltage-input, current-output programmable membership function generator circuit (MFC) using CMOS technology. It employs a voltage-to-current converter to provide the required current bias for the membership function circuit. The proposed MFC has several advantageous features. This MFC can be reconfigured to perform triangular, trapezoidal, S-shape, Z-Shape, and Gaussian membership forms. This membership function can be programmed in terms of its width, slope, and its center locations in its universe of discourses. The easily adjustable characteristics of the proposed circuit and its accuracy make it suitable for embedded system and industrial control applications. The proposed MFC is designed using the spice software, and simulation results are obtained

On Design and Implementation of Generic Fuzzy Logic Controllers

Soft computing techniques, unlike traditional deterministic logic based computing techniques, sometimes also called as hard computing, are tolerant of imprecision, uncertainty, and approximation. The primary inspiration for soft computing is the human mind and its ability to address day-to-day problems. The primary constituents of soft computing techniques are Artificial Neural Network, Fuzzy Logic Systems, and Evolutionary Computing. This thesis presents design and implementation of a generic hardware architecture based Type-IMamdani fuzzy logic controller (FLC) implemented on a programmable device, which can be remotely configured in real-time over Ethernet. This reconfigurability is added as a feature to existing FLCs in literature. It enables users to change parameters (those drive the FLC systems) in real-time and eliminate repeated hardware programming whenever there is a need. Realization of these systems in real-time is difficult as the computational complexity increases exponentially with an increase in the number of inputs. Hence challenge lies in reducing the Rulebase significantly such that the inference time and the throughput time is perceivable for real-time applications. To achieve these objectives, a modified thresholded fired rules hypercube (MT-FRHC) algorithm for Rulebase reduction is proposed and implemented. MT-FRHC reduces the useful rules without compromising system accuracy and improves the cycle time in terms of fuzzy logic operations per second (FzLOPS). It is imperative to understand that there are over sixty reconfigurable parameters, and it becomes an arduous task for a user to manage them. Therefore, a genetic algorithm based parameter extraction technique is proposed. This will help to develop a course tuning and provide default parameters that can be later fine-tuned by the users remotely through the Web-based User Interface. A hardware software codesign architecture for FLC is developed on TI C6748 DSP hardware with Sys/BIOS RTOS and seamlessly integrated with a webbased user interface (WebUI) for reconfigurability. Fuzzy systems employ defuzzifier to convert the fuzzy output into the real world crisp output. Centroid of Area (CoA) method is most widely used defuzzification method for control applications. However, the prevalent method of CoA computation is based on the principle of Riemann sum which is computationally complex. A vertices based CoA (VBCoA) defuzzification method is introduced. It has been observed that the proposed VBCoA method for COA computation is faster than the Riemann sum based CoA computation. A code optimization technique, exclusive to TI DSPs, is implemented to achieve memory and machine cycle optimization. The WebUI is developed in accordance to a client–server model using ASP.NET. It acquires fuzzy parameters from users, and a server application is dedicated to handling data communication between the hardware and the server. Testing and analysis of this hardware G-FLCS has been carried out by using hardware-in-loop test to control various system models in Simulink environment which includes water level control in a two tank system, intelligent cruise control system, speed control of an armature controlled DC motor and anti-windup control. The performance of the proposed G-FLCS is compared to Fuzzy Inference System of Matlab Fuzzy Logic Toolbox and PID controller in terms of settling time, transient time and steady state error. This proposed MT-FRHC based G-FLCS with VBCoA defuzzification implemented on C6748 DSP was finally deployed to control the radial position of plasma in Aditya Tokamak fusion reactor. The proposed G-FLCS is observed to deliver a smooth and fast system response

Design Of Dna Strand Displacement Based Circuits

DNA is the basic building block of any living organism. DNA is considered a popular candidate for future biological devices and circuits for solving genetic disorders and several other medical problems. With this objective in mind, this research aims at developing novel approaches for the design of DNA based circuits. There are many recent developments in the medical field such as the development of biological nanorobots, SMART drugs, and CRISPR-Cas9 technologies. There is a strong need for circuits that can work with these technologies and devices. DNA is considered a suitable candidate for designing such circuits because of the programmability of the DNA strands, small size, lightweight, known thermodynamics, higher parallelism, and exponentially reducing the cost of synthesizing techniques. The DNA strand displacement operation is useful in developing circuits with DNA strands. The circuit can be either a digital circuit, in which the logic high and logic low states of the DNA strand concentrations are considered as the signal, or it can be an analog circuit in which the concentration of the DNA strands itself will act as the signal. We developed novel approaches in this research for the design of digital, as well as analog circuits keeping in view of the number of DNA strands required for the circuit design. Towards this goal in the digital domain, we developed spatially localized DNA majority logic gates and an inverter logic gate that can be used with the existing seesaw based logic gates. The majority logic gates proposed in this research can considerably reduce the number of strands required in the design. The introduction of the logic inverter operation can translate the dual rail circuit architecture into a monorail architecture for the seesaw based logic circuits. It can also reduce the number of unique strands required for the design into approximately half. The reduction in the number of unique strands will consequently reduce the leakage reactions, circuit complexity, and cost associated with the DNA circuits. The real world biological inputs are analog in nature. If we can use those analog signals directly in the circuits, it can considerably reduce the resources required. Even though analog circuits are highly prone to noise, they are a perfect candidate for performing computations in the resource-limited environments, such as inside the cell. In the analog domain, we are developing a novel fuzzy inference engine using analog circuits such as the minimum gate, maximum gate, and fan-out gates. All the circuits discussed in this research were designed and tested in the Visual DSD software. The biological inputs are inherently fuzzy in nature, hence a fuzzy based system can play a vital role in future decision-making circuits. We hope that our research will be the first step towards realizing these larger goals. The ultimate aim of our research is to develop novel approaches for the design of circuits which can be used with the future biological devices to tackle many medical problems such as genetic disorders

Fuzzy Controllers

Trying to meet the requirements in the field, present book treats different fuzzy control architectures both in terms of the theoretical design and in terms of comparative validation studies in various applications, numerically simulated or experimentally developed. Through the subject matter and through the inter and multidisciplinary content, this book is addressed mainly to the researchers, doctoral students and students interested in developing new applications of intelligent control, but also to the people who want to become familiar with the control concepts based on fuzzy techniques. Bibliographic resources used to perform the work includes books and articles of present interest in the field, published in prestigious journals and publishing houses, and websites dedicated to various applications of fuzzy control. Its structure and the presented studies include the book in the category of those who make a direct connection between theoretical developments and practical applications, thereby constituting a real support for the specialists in artificial intelligence, modelling and control fields

Intelligent Computing: The Latest Advances, Challenges and Future

Computing is a critical driving force in the development of human civilization. In recent years, we have witnessed the emergence of intelligent computing, a new computing paradigm that is reshaping traditional computing and promoting digital revolution in the era of big data, artificial intelligence and internet-of-things with new computing theories, architectures, methods, systems, and applications. Intelligent computing has greatly broadened the scope of computing, extending it from traditional computing on data to increasingly diverse computing paradigms such as perceptual intelligence, cognitive intelligence, autonomous intelligence, and human-computer fusion intelligence. Intelligence and computing have undergone paths of different evolution and development for a long time but have become increasingly intertwined in recent years: intelligent computing is not only intelligence-oriented but also intelligence-driven. Such cross-fertilization has prompted the emergence and rapid advancement of intelligent computing. Intelligent computing is still in its infancy and an abundance of innovations in the theories, systems, and applications of intelligent computing are expected to occur soon. We present the first comprehensive survey of literature on intelligent computing, covering its theory fundamentals, the technological fusion of intelligence and computing, important applications, challenges, and future perspectives. We believe that this survey is highly timely and will provide a comprehensive reference and cast valuable insights into intelligent computing for academic and industrial researchers and practitioners

Application of fuzzy-sliding mode control and electronic load emulation to the robust control of motor drives

This thesis is concerned with the experimental investigation of robust speed control strategies for the industrial motor drive systems. The first objective of the thesis is to implement a high performance programmable dynamometer which can provide desired linear and non-linear mechanical loads for the experimental validation of the robust control methods. The discrete time implementation of the conventional dynamometer control strategy (the inverse model approach) is analysed and it is shown that this method suffers from the stability and noise problems. A new dynamometer control strategy, based on speed tracking and torque feedforward compensation, is developed and successfully implemented in the experimental system. The emulation is placed in a closed loop speed control system and the experimental results are compared with the corresponding ideal simulated results for the validation of the dynamometer control strategy. The comparisons show excellent agreement for a variety of linear and nonlinear mechanical load models and such a high performance experimental load emulation results are reported for the first time in research literature. The second objective of the project is to investigate the Fuzzy Logic Control (FLC) and the Sliding Mode Control (SMC) approaches in order to develop a simple,• algorithmic and practical robust control design procedure for industrial speed drive control systems. The Reaching Law Control (RLC) method, which is an approach to SMC design, and the FLC are used together in order to develop a practical robust speed control strategy. The robustness of the proposed control approach is tested for a variety of linear and non-linear mechanical loads provided by the dynamometer. Using the new robust control method, good output responses are obtained for large parameter variations and external disturbances

MATLAB

A well-known statement says that the PID controller is the "bread and butter" of the control engineer. This is indeed true, from a scientific standpoint. However, nowadays, in the era of computer science, when the paper and pencil have been replaced by the keyboard and the display of computers, one may equally say that MATLAB is the "bread" in the above statement. MATLAB has became a de facto tool for the modern system engineer. This book is written for both engineering students, as well as for practicing engineers. The wide range of applications in which MATLAB is the working framework, shows that it is a powerful, comprehensive and easy-to-use environment for performing technical computations. The book includes various excellent applications in which MATLAB is employed: from pure algebraic computations to data acquisition in real-life experiments, from control strategies to image processing algorithms, from graphical user interface design for educational purposes to Simulink embedded systems

Application of fuzzy-sliding mode control and electronic load emulation to the robust control of motor drives

This thesis is concerned with the experimental investigation of robust speed control strategies for the industrial motor drive systems. The first objective of the thesis is to implement a high performance programmable dynamometer which can provide desired linear and non-linear mechanical loads for the experimental validation of the robust control methods. The discrete time implementation of the conventional dynamometer control strategy (the inverse model approach) is analysed and it is shown that this method suffers from the stability and noise problems. A new dynamometer control strategy, based on speed tracking and torque feedforward compensation, is developed and successfully implemented in the experimental system. The emulation is placed in a closed loop speed control system and the experimental results are compared with the corresponding ideal simulated results for the validation of the dynamometer control strategy. The comparisons show excellent agreement for a variety of linear and nonlinear mechanical load models and such a high performance experimental load emulation results are reported for the first time in research literature. The second objective of the project is to investigate the Fuzzy Logic Control (FLC) and the Sliding Mode Control (SMC) approaches in order to develop a simple,• algorithmic and practical robust control design procedure for industrial speed drive control systems. The Reaching Law Control (RLC) method, which is an approach to SMC design, and the FLC are used together in order to develop a practical robust speed control strategy. The robustness of the proposed control approach is tested for a variety of linear and non-linear mechanical loads provided by the dynamometer. Using the new robust control method, good output responses are obtained for large parameter variations and external disturbances