Zero overshoot and fast transient response using a fuzzy logic controller

In some industrial process control systems it is desirable not to allow an overshoot beyond the setpoint or a threshold, this could be a safety constraint or the requirement of the system. This paper outlines our work in designing a fuzzy PID controller to achieve a step-response with zero overshoot while improving the output transient response. Our designed fuzzy PID controller is applied to stable, marginally stable and unstable systems and their step responses are compared with a tuned conventional PID controller. A comparative case study shows that the proposed fuzzy controller is highly effective and outperforms the PID controller in achieving a zero overshoot response and enhancing the output transient response

Design of Unmanned Underwater Vehicle (UUV) For Precision Targeting Using Simple PID-Controler

A model of an Unmanned Underwater Vehicle (UUV) for precision targeting using simple PID controller has been designed. The system has been assumed to have two-dimensional character, such that the mechanical control mechanism would be performed solely by rudder. A GPS/IMU system was employed in the model to provide the exact location and current trajectory direction and will be used to compared between the instantaneous correct direction and instantaneous current direction. This difference would drive PID control system to give correct angle deflection of the rudder. Some parameters of the PID controller has to be well-tuned employing several schemes including the Routh-Hurwitz stability criterion. Keywords: UUV, PID Controller, Precision Targeting, GPS, IM

Active force control of 3-RRR planar parallel manipulator

This paper presents a new and novel method to control a 3-RRR (revolute-revolute-revolute) planar parallel manipulator using an active force control (AFC) strategy. A traditional proportional-integral-derivative (PID) controller was first designed and developed to demonstrate the basic and stable response of the manipulator in performing trajectory tracking tasks. Later, the AFC section was incorporated into the control scheme in cascade form by adding it in series with the PID controller (PID+AFC), its primary aim of which is to improve the overall system dynamic performance particularly when the manipulator is subjected to different loading conditions. Results clearly illustrate the robustness and effectiveness of the proposed AFC-based scheme in rejecting the disturbances compared to the traditional PID controller

An optimized fractional order PID controller for suppressing vibration of AC motor

Fractional order Proportional-Integral-Derivative (PID) controller is composed of a number of integer order PID controllers. It is more accurate to control the complex system than the traditional integer order PID controller. The values of parameters of the fractional order PID controller play a decisive role for the control effect. Because the fractional order PID controller added two adjustable parameters than the traditional PID controller, it is very difficult to tune parameters. So the Back Propagation (BP) neural network is selected to optimize the parameters of the fractional order PID controller in order to obtain the high performance. Then the optimized fractional order PID controller and the traditional PID controller are used to control AC motor speed governing system. And the vibration spectrum and stator current spectrum under different rotating speeds are compared and analyzed in detail. The results show that the optimized fractional order PID controller has better vibration suppression performance than the traditional PID controller. The reason is that the optimized fractional order PID controller changed the stator current component, and further changed the frequency components and the amplitude of the vibration signal of the motor

System identification and pid control of toothbrush simulator system

Toothbrush simulator was invented for industry and dentist researchers to do research related to plaque removal. The toothbrush simulator system repeatedly has a problem in achieving the desired speed control. The brushing movement is inconsistence and stops eventually if there is a force exerted on the toothbrush holder. Further research is required to increase the reliability and controllability of the speed response achievable from the toothbrush simulator system. In this study, a PID controller is designed and embedded in the system. A real-time experiment has been conducted on the real system via the Matlab Simulink environment to construct the model. The model parameters are optimized with model order 2, 3 and 4 where each model order has been analyzed for ten (10) times iteration by the genetic algorithm in obtaining the accurate transfer function. The model has been validated through correlation analysis. The PID controller was tuned through the PID tuner and Ziegler-Nichols method. Simulated and real-time system response from both tuning methods was compared. The simulated response with the selected PID controller is then compared with the response from the real-time experiment. The closed-loop system without controller was compared with the response with the PID controller. The PID controller was then deployed into the real system by uploaded into the microcontroller. The brushing simulator remote control was created to control the desired speed through a smartphone. Genetic algorithm model based on model order 4 has been selected as the best model as it able to achieve the minimum MSE value of 0.0176 and past all the validation tests. The selected PID parameters was from PID tuner tuning method with gain values of; Kp= 17.9287, Ki= 40.751 and Kd= -0.52705. Both results of simulation and real-time tests were compared, and they show about similar performances. The controlled system response had achieved all five desired speed of 175, 195, 215, 235 and 255 rpm with the percentage of improvement 67%, 65%, 65%, 65%, and 68%. Throughout this study, a genetic algorithm model based and tuned PID controller parameters has been applied to the real system improvised in better system response

Robust PID tuning. Application to a Mobile Robot Pathtraking problem.

IFAC Digital Control: Past,Present and Future of PlO Control.Terrassa.Spain.2000This paper presents a methodology for tuning PIDs considering the nominal performance and the robustness as control specifications. The synthesis procedure is similar to the Ziegler-Nichols method for PID controllers and can be easily used for industrial processes. As a workbench for testing the PID controller a mobile robot has been used. The path tracking problem of a mobile robot has been used as a workbench for testing the PID controller

Understanding and Design of an Arduino-based PID Controller

This thesis presents research and design of a Proportional, Integral, and Derivative (PID) controller that uses a microcontroller (Arduino) platform. The research part discusses the structure of a PID algorithm with some motivating work already performed with the Arduino-based PID controller from various fields. An inexpensive Arduino-based PID controller designed in the laboratory to control the temperature, consists of hardware parts: Arduino UNO, thermoelectric cooler, and electronic components while the software portion includes C/C++ programming. The PID parameters for a particular controller are found manually. The role of different PID parameters is discussed with the subsequent comparison between different modes of PID controllers. The designed system can effectively measure the temperature with an error of ± 0.6℃ while a stable temperature control with only slight deviation from the desired value (setpoint) is achieved. The designed system and concepts learned from the control system serve in pursuing inexpensive and precise ways to control physical parameters within a desired range in our laboratory

Suppression of Parkinson's hand-like tremor using fuzzy-PID controller

This paper presents the performance evaluation of an active vibration technique in suppressing human hand tremor. A PID integrated with fuzzy logic controller is proposed to control a linear electromagnet actuator and then applied onto a four Degree-of-Freedoms (DOFs) biodynamic model which emulate a Parkinson Disease (PD) hand. Heuristic method is employed in searching for appropriate parameters values for the proposed controller. Then, a comparative study between the performances of Fuzzy-PID controller and conventional PID controller tuned using Ziegler-Nichols method is done. The simulation study results demonstrates a comparable performance between Fuzzy-PID controller and conventional PID controller. Fuzzy-PID controller was effectively attenuated about 96.77% of initial tremor magnitude while for the PID controller is about 89.37%