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This research paper focuses on the design and analysis of the longitudinal trajectory control system for carrier-based F-18 aircraft. The study aims to deepen the understanding of trajectory control structures and the complexities involved in parameter design, while also enhancing proficiency in using the Matlab/Simulink environment for control applications. The research investigates the challenges associated with crafting effective control systems for carrier-based aircraft, with a particular emphasis on optimizing the longitudinal axis for precision. The paper presents a step-by-step approach, including the establishment of an aircraft model in state-space form, the design of stability augmented and PID controllers, and the implementation of glide slope tracking control. Simulation results demonstrate the system's ability to correct glide path deviations and ensure accurate landings. The study provides valuable insights into the design and optimization of autonomous landing systems for carrier-based aircraft. [ABSTRACT FROM AUTHOR]

Manual driving is being gradually replaced by autonomous driving technology. Compared to manual driving, autonomous driving performs better in many regions such as accuracy and holistic planning. A cruise control system is the core component of the auto-driving system, it collects information from multiple sensors and makes a response to its servo motors in no more than 100 µs. However, traditional motor collaborative control methods are usually inefficient and difficult to adapt to practical applications. When the system collects a signal, it takes a short period to raise the response from zero and a period to oscillate. Engineers improve the whole response circuit to shorten those two periods of time, which makes the system sensitive. Most traditional PID controllers show relatively agile response, but for a driving system, they are usually too complex and expensive. To maintain the necessary function and to decrease the cost, this research designed a circuit and tested it in simulation software. To prove that the new system is cheaper to manufacture than traditional ones, the circuit is also physically assembled. This research shows a new advanced PD control system, which shows quick response and smooth oscillation. All simulation results showed the effectiveness of the PD controller. This study is of great significance for improving the cruise control performance of automobiles. The improved PD controlling circuit could also be applied to other fields of automated control, to relieve the installation and overhaul work of those IOT products as well. [ABSTRACT FROM AUTHOR]

With the development of science and technology, UAV technology and application have become an increasingly important field. The four-rotor aircraft has a simple structure and diverse functions and has been widely used in many fields. In practical applications, it is necessary to strictly ensure the stability of its flight, so it is very important to ensure stability when designing the control system. Knowing that the PID control algorithm can improve the stability of the system by adjusting various parameters, and the response speed is fast and easy to realize, this paper adopts the PID control method to design a stable quadrotor aircraft system. In this paper, the mathematical model of the four-rotor aircraft is first established according to the dynamics theory, and its system composition and working principle are shown, which lays a structural foundation for the subsequent design. After that, the basic principle and function of PID control are expounded, and the corresponding controller is designed based on the algorithm in the four attitude directions of vertical, pitch, roll, and yaw. Finally, the control system is simulated by establishing a model on Simulink and inputting appropriate parameters. The results show that the speed of the PID controller can meet the corresponding control requirements in the simulation of four channels, which indicates that the design method is feasible and can guarantee the stability of the system. This study verifies the effectiveness of PID control of four-wing rotary-wing UAVs and provides a basis for further exploration of algorithm improvement and innovation and improvement of aircraft stability. [ABSTRACT FROM AUTHOR]

In recent years, the popularity of electric vehicles has reduced dependence on oil, sparking concerns about oil supply and environmental issues. Pure electric vehicles are representative of new energy vehicles due to their low pollution, low noise, and high efficiency. Electric motors drive them and have flexibility at different speeds. PID controllers are widely used to control DC motors in electric vehicles, but there are control and circuit issues. This article proposes a DC motor PID control system based on PID control and Falstad, which reduces the number of operational amplifiers through circuit simplification while keeping the components in line with the general order of magnitude. The characteristics of operational amplifiers make them suitable for simulating known transfer functions. This article introduces the modeling and simulation methods and circuit optimization schemes of DC motors. These studies contribute to improving the performance and maintainability of DC motors in electric vehicles and promoting the development of new energy vehicle technology. [ABSTRACT FROM AUTHOR]

The DC servo motor is widely utilized within several domains, including aerospace, mechanical engineering, and robotics control, among others. As such, studies of position control for DC servo motors carry significant significance. It should be noted that the choice of the controller holds considerable sway over the responsiveness of the motor, with suboptimal selections made based on intuition rather than analysis. Therefore, this study aims to establish a model of a DC servo motor system and to simulate and compare it in different cases. One is a motor system without any additional controller, while the other system uses a PID controller, which effectively optimizes the transient response of the DC servo motor. In this paper, the DC servo motor system is simulated using Falstad, and the optimum PID control coefficients are obtained using MATLAB. The step signal waveforms are observed to verify the improvement of the PID controller in terms of system accuracy and performance. The simulation results show that the PID controller can effectively reduce fluctuations and achieve a fast response and high-accuracy control system compared to conventional proportional controllers. The research in this paper enables us to determine the optimal control method to improve control performance and deepen our understanding of its effect on the stability of DC servomotors. [ABSTRACT FROM AUTHOR]

With the continuous development of unmanned aerial vehicles, the application of unmanned aerial vehicles in the fields of livelihood and military is expanding. The research related to the control of unmanned aerial vehicles has increased accordingly. Conventional proportional-integral-derivative control (PID) control has poor stability and robustness. In this paper, a framework for unmanned aerial vehicle altitude control system is proposed and a design of unmanned aerial vehicle motor speed control system based on PID control is given. In this study, the PID controller is tuned using zero-pole plot analysis and group comparison analysis. The desired system response is obtained, and the stability and robustness of the system are increased. The system remains stable when it receives transient or continuous perturbations. This study gives a solution to the field of unmanned aerial vehicle altitude control and motor speed control. This study is also informative for learners and researchers in the field of PID control and unmanned aerial vehicle control. [ABSTRACT FROM AUTHOR]

At present, autonomous vehicle is becoming a popular means of transportation, and can gradually become the public choice of transportation. However, autonomous vehicles still face numerous technical challenges. Due to the influence of different forces during the driving process of a car, there are different situations during the starting stage of the car. When approaching the target speed, there may be shaking or difficulty in reaching the target value. Therefore, the PID controller method is adopted to regulate it. This paper focuses on the research of the starting stage of an autonomous vehicle and uses Simulink and MATLAB for analysis. PID controller is used to adjust the parameters of its starting stage. This paper first analyzes the force on the moving vehicle and lists the function formula. Then, this paper puts forward a method of PID controller based on Simulink to adjust the starting parameters of autonomous vehicles. The simulation experiment shows the advantages of the PID controller system, for example, the accuracy can be higher and the response speed can be faster. This study is of great significance for the starting stage of autonomous vehicles. [ABSTRACT FROM AUTHOR]

Unmanned Aerial Vehicles have evolved from their military origins to a wide range of civilian and commercial uses. However, commercial uses have a higher occupation. This means that civilian uses have high exploitability. The low number of civilian Unmanned Aerial Vehicles is largely dependent on the fact that they are expensive and have few counterparts. However, they have the advantage of being fast and unaffected by urban traffic. An Unmanned Aerial Vehicle with path planning modules and flight controllers makes it possible to transport goods within cities. According to this situation, this paper introduces a possible application to the logistics industry. Urban areas usually have a high demand for the logistics industry. The security and efficiency of delivery are the most significant issues for people in urban areas. However, the traditional control method of UAVs is time-consuming and laborious. Therefore, a new combination method to control a UAV is proposed in this paper. The functions and simulation in this paper provide the feasibility of using the new combination method to control a UAV. In the simulation, a UAV can fly from the start point to the destination steadily. All the obstacles on the map are avoided. This means a UAV can deliver packages with this technology. This study gives a new potential for UAVs in civilian uses, which also improves the existing delivery method. [ABSTRACT FROM AUTHOR]

Utilizing bio-oils in liquid pumping unites are considered as a one of the most important parts in the water filtration and pumping stations especially in the area of automatic control. In this paper using bio-oils are being investigated which have high degradability and it is environmentally friendly. The thermal performance features of the liquid pumping unit lubricated with bio sunflower seed vegetable oil was investigated and compared with the performance features with mineral oil (MO10W-30). The study includes, oil temperature, density, power and tourq under different rational speed (1200-1500 rpm) for the pump. From experimental investigations carried out in this study, it can be concluded that biodegradable vegetable oils are adequate alternative to the mineral oil as a renewable bio cooling and lubricate. An automatic pumping unit was implemented (three tanks one as a source and two auxiliary) based on two types of controllers. These two are: PID controller and artificial neural networks. The results in neural back propagation that more accurate than PID controller. The over shoot is improving in artificial network is zero where compare with PID result 0.8 m3/s flow rate [ABSTRACT FROM AUTHOR]

Direct current (DC) servo motors the common motors which is used in many applications, especially position control system. To maintain line of sight required for good communication, particularly in satellite tracking. PID controller is still used in many applications. In this paper, the main objective is designing and controlling of an antenna position system based on a DC servo motor. The first aim is driving the transfer function of the proposed system and test the stability of speed and position of motor. The results which are obtained by using the MATLAB / SIMULINK program shows that the PID controller-based Ziegler and Nichols method gave an efficient performance, completely stability of the performance of the DC servo motor. It is possible to follow the methodology of the current research to calculate the gains parameter of PID controller. [ABSTRACT FROM AUTHOR]

The current study focused on the use of two types of control systems, the traditional control algorithm (PID) and the expert control algorithm (ANN). In the current work it was proposed to use the 2Ph-HSM motor for its importance in industrial applications. The grinding process is one of the industrial applications that has been simulated The system is completed by using a motor to perform the grinding process and improve its performance using control systems. Through the simulation results, it can be confirmed the possibility of improving the working performance of the electric motor and arriving at a suitable design for control systems for the speed and location of the motor with different conditions, which simulate real time. the current work aims to conduct a simulation suitable for the work of the electric motor that moves a robot arm, which needs to adjust the position and speed of its movement to put it in an application for the grinding process of a steam fan, which generates the need to use a robot. Control needs to be tested to obtain the best performance. The proposal of the neural network and the traditional method for controlling the speed and position of the rotor of the arm motor. All the expected cases that simulate real time were performed. The researchers reached through the simulation results to the possibility of improving the system's functionality by using neural networks better than the traditional according to standards such as speed and accuracy of response and time of rise and overtaking. [ABSTRACT FROM AUTHOR]

PID controller is the most controllers used in many applications. Tuning process for the gains of PID controllers is time consuming, not easy and generally lead to poor performance especially with non-linear systems. This paper presents an antenna azimuth position system controlled by PID tuner where, its computes an initial compensator design for the linearized plant model using the algorithm described in PID tuner algorithm in MATLAB Simulink model. The simulation results show that the PID tuner controller is better method than the conventional tuning method. Where it's given accurate and fast results for gain values and all performance values (settling Tim, over shot, rising time, peak time, and steady stat error) for a proposed system. [ABSTRACT FROM AUTHOR]

In this study, a cart with an inverted pendulum subjected to disturbance powers performed stability control utilizing eyewitness-based (observer-based) and Proportional-Integral-Derivative (PID) controllers. The Lagrangian relation has been utilized to structure the framework motions equations and framework linearizing to the nonlinear high-order dynamic system. The objective of the suggested versatile fluctuation regulator is for maintaining the operation time power control activity of the inverted pendulum in the ongoing to definitively and straightaway fluctuate the pendulum reaches to inverted location. In this work, an upgraded composed suggested controller has been acquainted with controlling the reaction of the nonlinear inverted pendulum qualities within the sight of an outer unsettling influence signal Y. The frame stability comparison is examined by the simulation. The proposed controllers have been compared by adopting the Matlab_2020b program. The output responses are effectively determined. The comparison results of using the proposed observer-based controller (OBC) showed an improvement in depressing the oscillation overshooting and reducing settling time by 41.8% and 40.3 % respectively compared with the results obtained by using the PID controller. [ABSTRACT FROM AUTHOR]

How to accurately direct a mobile robot to follow a certain path is the main problem with line follower robots. The design and execution of an intricate line follower mission are demonstrated in this research using Matlab Simulink. Using software that simulates the motion of a mobile robot along a complex path, the proposed line follower algorithm and the offered PID controller are developed and evaluated. Due to the difficulty in selecting the PID controller's settings, the Particle Swarm Optimization (PSO) approach is utilized to choose and optimize the parameters of the constructed PID controller. Three IR sensors are used to collect data on the mobile robot's position in respect to the intended path. The yaw rate of the mobile robot will be controlled to maintain it on the planned route by changing the speed of the actuators. The simulation findings show that a mobile robot's mobility may be maintained even when undertaking complex maneuvers. The hardware design of the robot system is completed using the mobile robot. The real-world results show that a mobile robot and a simulation function almost identically. The yaw rate of the mobile robot will be controlled to maintain it on the planned route by changing the speed of the actuators. The simulation findings show that a mobile robot's mobility may be maintained even when undertaking complex maneuvers. The hardware design of the robot system is completed using the mobile robot. The real-world results show that a mobile robot and a simulation function almost identically. [ABSTRACT FROM AUTHOR]

In this research, we examine how well the controller we can develop controlled load frequency characteristics of a four-area system. In light of this, a (PID) proportional-integral-derivative controller for the proposed transit search algorithm (TSA) is built, and its effect on the performance of the LFC is demonstrated. The reliability and universality of the outputs from the popular PID controller necessitate their use in this investigation. As a result of its efficient execution of exploration and exploitation tasks, the proposed TSA algorithm can generate viable options for resolving the problem. In the terms of settling time ts, peak variance tp, and oscillation magnitude Mp, the TSA-based PID controller was shown to be the better in the simulation results. [ABSTRACT FROM AUTHOR]

This project outlines the construction of a Fuzzy algorithm-based PID-type (Proportional-Integral-Derivative) controller using VHDL for use in transportation cruising systems. To prevent roadside collisions between vehicles, the Fuzzy concept cruising system was created. The developed fuzzy logic controller (FLC) acts as a manual for changing the vehicle's speed up or down. The controlling speed is based on the distance from the preceding vehicle when a vehicle is too close or has to be warned. In this paper, Implementation of a fuzzy PID controller for internet of vehicles (IOV) transportation utilizing FPGA is implemented. The IOV-based traffic management enables communication between the vehicle and its internal and exterior environments, facilitating interaction between the vehicle and people, other vehicles, and third parties. A fuzzy PID controller is created for vehicle-to-vehicle communication in order to prevent collisions. The vehicle will notify a third party, such as a police patrol or ambulance, if it is involved in an accident. Its informed through the GPS coordinates that the car sends. [ABSTRACT FROM AUTHOR]

In this paper, the classical PID regulator depending on the modern optimization mechanism of the water cycle optimization (WCO) is presented as a regulator for two areas of hydrothermal (TAHT) power system (TAHTPS). However, the presented regulator efficacy is demonstrated with I and PI for the same disturbance in step load (SLD) of 10% on area-1. Moreover, the sovereignty of WCA optimized PID is validated by other approaches listed in recent literature. Further, TAHTPS is integrated with a unified power flow controller (UPFC) to dampen deviations and superconducting magnetic energy storage (SMES) in each control region. Simulation results deliberately the performance of the UPFC-SMES strategy in regulating the frequency of TAHTPS. [ABSTRACT FROM AUTHOR]

The Thomas Jefferson National Accelerator Facility collaborates with Lawrence Berkeley National Lab to implement a dynamic UDP load balancer (LB) for high-throughput scientific data processing. This study employs a simulation to compare the efficacy of Proportional, Integrative, Derivative (PID) controllers and Q-Learning based controllers for configuring the load balancer. Two cluster configurations, homogeneous and heterogeneous, were examined. The simulation results indicate that PID control is superior in both configurations. In homogeneous clusters, PID achieved a 50% reduction in aggregate queue levels and maintained an even distribution across computational nodes (CNs). In contrast, Q-Learning was less effective in heterogeneous environments, exacerbating queue levels compared to the no-control case and failing to achieve balance across the cluster. Our findings suggest that PID control should be used for the ESnet-JLab FPGA Accelerated Transport (EJFAT) system. [ABSTRACT FROM AUTHOR]

Particle identification (PID) is one of the most fundamental tools in various physics research conducted in collider experiments. In recent years, machine learning methods have gradually become one of the mainstream methods in the PID field of high-energy physics experiments, often providing superior performance. The emergence of quantum machine learning may potential arm a powerful new toolbox for machine learning. In this work, targeting at the π±/K± discrimination problem at the STCF experiment, a convolutional neural network (CNN) in the endcap PID system is developed. By combining the hit position and arrival time of each Cherenkov photon at the sensors, a two-dimensional pixel map is constructed as the CNN input. The preliminary results show that the CNN model has a promising performance. In addition, based on the classical CNN, a quantum convolution neural network (QCNN) is developed as well, exploring possible quantum advantages provided by quantum machine learning methods. [ABSTRACT FROM AUTHOR]

The behaviour of the power system varies as the wind power penetration increases. Wind turbine generators must adhere to essential grid code, which requires them to maintain grid connectivity even in the event of an abnormal circumstance. In this study, a unique wind energy conversion system (WECS) based on a doubly fed induction generator is suggested, which includes a superconducting fault current limiter (SFCL) and a dynamic voltage restorer (DVR). The DVR improves the power quality of the system and increases its Low Voltage Ride through (LVRT) capability. By utilizing SFCL, fault current can be reduced effectively, which lowers the cost of high capacity circuit breaker. In this study, a resistive SFCL is developed to enhance the power system's Fault Ride through (FRT) capability. It is also required to maintain the DC link capacitor voltage stable in DFIG based WECS. Additionally, this study employs a PID controller to lessen DC link voltage fluctuations during faults. All of these processes have been modelled with the aid of a simulation programme that uses MATLAB and built in Simulink library components. [ABSTRACT FROM AUTHOR]

The aim of this study is to develop a novel method for controlling the heart rates of people with atrial fibrillation who are being treated with pacemaker devices. To achieve the system's goals, the P and PID controller methods are used. In all, there are forty personnel spread over two sets of controllers: proportional (P) and proportional (PID) controllers. The current parameters for the sample size are as follows: 80% significance, 80% Gpower, 80% confidence, 95% confidence, and a 1% enrollment ratio. Overshoot, rise/fall/settling times, and peak/settling times are some of the metrics used to assess the performance of P and PID controllers. Rise Time, Peak Time, Settling Time, and Overshoot averaged 0.0633, 0.0633, 6.1700, and 48.2290 for the proportional controller (P). Rise Time (0.0586), Peak Time (0.0586), Settling Time (7.1667), and Overshoot (51.0441) were often seen in PID controllers. Independent sample T-test results suggested that the Proportional Integral Derivative (PID) Controller was slightly more effective than the Proportional (P) Controller, but after examining all of the relevant factors, we were unable to identify a statistically significant difference between the two groups. [ABSTRACT FROM AUTHOR]

This study intends to create a novel heart rate regulation technique for pacemaker-using atrial fibrillation patients. This study will focus on people in this situation. System uses Proportional controller (P) and Proportional Integral Derivative (PID) controllers. The PID controller controls the control group, whereas the P controller manages research. The following categories and subcategories describe sample size features: The enrollment ratio and cutoff must be one and 0.05. Gpower is required for 80% of the population. Rise Time, Peak Time, Settling Time, and Overshoot assess proportional (P) and PID control efficacy. Overshoot is the sixth time to evaluate proportional (P) and PID controllers. The sixth choice is overshoot. The proportional controller's Rise and Peak averaged 0.0633, Settling 6.1700, and Overshoot 48.2290. (P). In a proportional integral derivative (PID) controller, rising, peak, settling, and overshoot times were 0.0586, 0.0586, 7.1667, and 51.0441 milliseconds, respectively. An independent sample T-test suggested that the Proportional Integral Derivative (PID) Controller was somewhat better than the Proportional (P) Controller, although other parameters were similar between the two groups (p>0.05). This showed that the PID Controller is not much superior than the P Controller. [ABSTRACT FROM AUTHOR]

The control device of a vehicle's anti-lock braking system (ABS) most commonly implements two-position control. In modern automation systems, many other control laws are used, which in certain cases are much better than the two-position control. This article discusses the development of a fuzzy PID controller for the control of an ABS. The fuzzy PID controller is tuned using the optimization method, which employs a genetic algorithm to determine the optimal solution. A comparison is made between the transient processes in the ABS control device with a two-position controller, a PID controller and a fuzzy PID controller, and the robustness of the system is evaluated. The 14 s braking time for the two-position controller decreases to 13 s when operating with a PID controller and to 11 s when operating with a fuzzy controller, which represents a 25% reduction in braking time, and therefore a shorter braking distance. The developed fuzzy controller also provides a better system robustness and will reduce pressure fluctuations in the pipes. [ABSTRACT FROM AUTHOR]

Robotics has been widely used in education as a learning tool to attract and motivate students to conduct laboratory experiments in the context of mechatronics, electronics, microcomputers, and control. In this paper, we propose the implementation of a PID control algorithm for a Self-Balancing Bike. The algorithm is implemented on the Arduino Uno microcontroller. The robot should be able to maintain its balance condition while moving. To achieve this goal, we use the MPU6050 gyroscope sensor to read the tilt conditions and use a servo to move the robot's steering wheel which will be used to control the robot's balanced position. From the experiments, the proposed PID controller shows acceptable performance for the robot to maintain its balance position at a given tilt setpoint. [ABSTRACT FROM AUTHOR]

Second-order unstable processes are frequently encountered in process industries. The higher-order process dynamics are approximated to second-order processes in order to design a controller. In industrial processes, Proportional Integral Deriva-tive(PID) controllers are still widely used controllers. PID, cascaded with filters provides satisfactory closed-loop performance for unstable processes. The present work proposes a PID controller cascaded with a fourth-order filter for an unstable Second Order Process with Time Delay(SOPTD). A polynomial approach is used to estimate the controller and filter parameters analytically. For the time delay approximation, a higher-order Laguerre shift is utilized. The Maximum Sensitivity(MS) criterion is used in order to calculate the tuning parameter(λ). To reduce servo response overshoots, a set point filter is chosen. The present method is compared with other reported methods using various performance indices. [ABSTRACT FROM AUTHOR]

The major contribution of this paper is shows how to control the speed of Permanent Magnet Synchronous Motor (PMSM) by using Proportional Integral and Derivative (PID) controller. In this work, proposed PID controller is used in both speed and current feedback loops to control the speed and torque respectively. The proposed PID controller having the advantages which are less oscillatory response, less overshoots and takes less settling time for the speed response compared with existing PID controller used in speed control loop. The PMSM drive is used in electric vehicle, electric traction, robotics and industrial dive applications. The PMSM having the salient features which are high efficiency, high torque density, low torque ripple, high power density and robust construction compare to dc, induction, Switched Reluctance Motor (SRM) and Brush Less Direct Current (BLDC) motors. In this paper, the proposed PID controller is developed based on Field Oriented Control (FOC) strategy is well used to achieve the good speed response of PMSM drive using MATLAB R2019b/Simulink software. The proposed PID controller provides an excellent steady state and dynamic speed response in terms of rise time, peak time, settling time and overshoots. In addition, proposed PID controller has overcome the drawbacks of Proportional (P) and Proportional Integral (PI) controllers. The P and PI controllers which process only first order unstable systems can be stabilized and higher order processes cannot be stabilized respectively. These controllers compromised if the system dynamics change over time. [ABSTRACT FROM AUTHOR]

In this paper, PID controller design for interval modelled Cuk converter is proposed by reduced order (RO) modelling. The reduction of interval modelled higher order (HO) Cuk converter into first order model is done with the help of Routh-Padé approximation and matching of time moments (TMs) and Markov parameters (MPs). The Routh-Padé approximation technique is utilized for determination of denominator coefficients of desired reduced order model (ROM). The ascertainment of numerator coefficients is accomplished using TMs and MPs matching in between HO system and desired ROM. The controller design is done by minimizing the integral-square-error (ISE) with the help of the Jaya algorithm. ISE is framed by utilizing alpha and beta parameters. The step responses are provided to prove the efficacy and superiority of the proposed method. The tabulated values in terms of error indices are also provided for comparative analysis in the support of proposed method. [ABSTRACT FROM AUTHOR]

The problem in two-wheeled vehicles is the lack of vehicle stability when getting a sudden force disturbance, especially at low speed and stationery. In this study, stabilization of a two-wheeled self-balancing vehicle prototype is performed by using a control moment gyroscope and PID controller. The gyroscopic effects of two flywheels mounting on a gimbal are used to generate control torque to maintain the vehicle in the upright equilibrium position. First, a dynamic model is derived using the Euler Lagrange formulation for the controller design. The prototype using an Arduino microcontroller is developed, and an Inertia Measurement Unit is used to measure the orientation, which is used for feedback. The designed controller can maintain the prototype in the upright unstable equilibrium position. [ABSTRACT FROM AUTHOR]

This research examines the effects of fuzzy control methods and proportional-integral-derivative (PID) on the performance of Permanent Magnet Direct Current (PMDC) motors. It is possible to get a general idea of each controller's efficiency by comparing the two of them. According to the study of the literature, many researchers used traditional (PID) controllers to regulate the speed of (PMDC) motors. It is challenging to manage the parameter values in a conventional PID controller and obtain excellent, suitable characteristics. However, there are some drawbacks to the PID controller, including a high beginning overshoot, susceptibility to controller gains, and a slow reaction to unexpected disturbances. To surmount the drawbacks of the traditional PID controller, a reasonably designed PID controller with a computational optimization approach technique is suggested. Additionally, fuzzy logic-based controllers, specifically fuzzy control, are suggested in this research, and their effectiveness is compared with that of PID controllers. Results from all operators' simulations are shown and examined. When controlling the speed of (PMDC) motors, it is found that fuzzy controllers perform better than other controllers. Using MATLAB modeling, we concluded that the suggested controller would result in a faster settling time, as well as a reduced overshoot and steady-state error. [ABSTRACT FROM AUTHOR]

Model-based controllers must be created by modelling the system to be controlled. This is because, regardless of how well-tuned the controller's settings are based on this model, good control performance cannot be predicted without first picking the suitable model for the process. The vast majority of industrial processes are overdamped, time-delayed steady-state systems. Designing a non-linear controller has always been difficult for researchers and control professionals. The robotic manipulators have numerous inputs and outputs. A Nonlinear PID Controller has been designed in this paper. This controller combines the Proportional Integral and Derivative controllers, as well as a nonlinear factor that multiplies with the integral controller. After Simulink modelling the controller, it was discovered that its performance is superior to that of other current controllers, and that its application is ubiquitous. [ABSTRACT FROM AUTHOR]

The robotic manipulator system has demonstrated its efficacy in a variety of fields. As a result, it is essential to design an efficient controller for managing the end position of a robotic arm. Due to the rising nonlinearity and complexity of robotic manipulator systems, a typical proportional-integral-derivative controller has proven ineffective. In recent years, intelligent techniques such as fuzzy logic, neural networks, and optimization algorithms have emerged as a potent tool for managing extremely complex nonlinear processes with uncertain dynamics. In this study, a PID Controller and a Fuzzy Proportional-Integral-Derivative controller with parameters generated by a Genetic Algorithm using Absolute Error Integral as the goal function are created. In this paper, simulated output results of plants controlled by a Fuzzy ProportionalIntegralDerivative controller are presented, and the superiority of the implemented controller is demonstrated through a comparison with a conventional Proportional-Integral-Derivative controller using the Genetic Algorithm optimization technique. [ABSTRACT FROM AUTHOR]