Optimal PID Control of a Brushed DC Motor with an Embedded Low-Cost Magnetic Quadrature Encoder for Improved Step Overshoot and Undershoot Responses in a Mobile Robot Application

The development of a proportional–integral–derivative (PID) control system is a simple, practical, highly effective method used to control the angular rotational velocity of electric motors. This paper describes the optimization of the PID control of a brushed DC motor (BDCM) with an embedded low-cost magnetic quadrature encoder. This paper demonstrates empirically that the feedback provided by low-cost magnetic encoders produces some inaccuracies and control artifacts that are not usually considered in simulations, proposing a practical optimization approach in order to improve the step overshoot and undershoot controller response. This optimization approach is responsible for the motion performances of a human-sized omnidirectional mobile robot using three motorized omnidirectional wheels

On the design and implementation of a control system processor

In general digital control algorithms are multi-input multi-output (MIMO) recursive digital filters, but there are particular numerical requirements in control system processing for which standard processor devices are not well suited, in particular arising in systems with high sample rates. There is therefore a clear need to understand the numerical requirements properly, to identity optimised forms for implementing control laws, and to translate these into efficient processor architectures. By taking a considered view of the numerical and calculation requirements of control algorithms, it is possible to consider special purpose processors that provide well-targeted support of control laws. This thesis describes a compact, high-speed, special-purpose processor which offers a low-cost solution to implementing linear time invariant controllers. [Continues.

Developing FPGA-based Embedded Controllers Using Matlab/Simulink

Field Programmable Gate Arrays (FPGAs) are emerging as suitable platforms for implementing embedded control systems. FPGAs offer advantages such as high performance and concurrent computing which makes them attractive in many embedded applications. As reconfigurable devices, they can be used to build the hardware and software components of an embedded system on a single chip. Traditional FPGA design flows and tools, requiring the use of Hardware Description Languages (HDLs), are in a different domain than standard control system design tools such as MATLAB/Simulink. This paper illustrates development of FPGA-based controllers by utilizing popular tools such as MATLAB/Simulink available for the design and development of control systems. The capability of DSP Builder is extended by developing a custom library of control system building blocks that facilitates rapid development of FPGA-based controllers in the familiar Matlab/Simulink environment. As a case study, this paper presents how the tools can be utilized to develop a FPGA-based controller for a laboratory scale air levitation system

Dual Design PID Controller for Robotic Manipulator Application

This research introduces a dual design proportional–integral–derivative (PID) controller architecture process that aims to improve system performance by reducing overshoot and conserving electrical energy. The dual design PID controller uses real-time error and one-time step delay to adjust the confidence weights of the controller, leading to improved performance in reducing overshoot and saving electrical energy. To evaluate the effectiveness of the dual design PID controller, experiments were conducted to compare it with the PID controller using least overshoot tuning by Chien–Hrones–Reswick (CHR)  technique. The results showed that the dual design PID controller was more effective at reducing overshoot and saving electrical energy. A case study was also conducted as part of this research, and it demonstrated that the system performed better when using the dual design PID controller. Overshoot and electrical energy consumption are common issues in systems that can impact performance, and the dual design PID controller architecture process provides a solution to these issues by reducing overshoot and saving electrical energy. The dual design PID controller offers a new technique for addressing these issues and improving system performance. In summary, this research presents a new technique for addressing overshoot and electrical energy consumption in systems through the use of a dual design PID controller. The dual design PID controller architecture process was found to be an effective solution for reducing overshoot and saving electrical energy in systems, as demonstrated by the experiments and case study conducted as part of this research. The dual design PID controller presents a promising solution for improving system performance by addressing the issues of overshoot and electrical energy consumption

Intelligent UPS Inverter Control Design Using Microcontroller

This paper presents many control algorithms using microcontroller for an uninterruptible power supply (UPS) inverter, in order to provide pure sinusoidal wave 50 Hz, controlled by the PIC-microcontroller. The strategy is to utilize the PIC microcontroller and its special features in controlling the UPS inverter. The first approach accomplished with a classical control Proportional-Integral-Derivative (PID) algorithm. The second approach accomplished with the Fuzzy Logic Control (FLC). The third approach accomplished with nonlinear PID-fuzzy logic controller. The ability of the proposed scheme is validated via a successful implementation on a microcontroller-based UPS inverter. The proposed scheme has shown its robustness on low output voltage distortion, excellent voltage regulation, and it is insensitive to load variation, even under nonlinear loads. Experimental studies are performed to further validate the effectiveness of this scheme. This system may be used with grid-solar energy systems. Keywords: PID Controller, Fuzzy Logic Control, Nonlinear PID-Fuzzy Logic, Takagi Sugeno, Microcontroller Application

Implementation of an extended prediction self-adaptive controller using LabVIEW (TM)

The implementation of the Extended Prediction Self-Adaptive Controller is presented in this paper. It employs LabVIEWTM graphical programming of industrial equipment and it is suitable for controlling fast processes. Three different systems are used for implementing the control algorithm. The research regarding the controller design using graphical programming demonstrates that a single advanced control application can run on Windows, real time operating systems and FPGA targets without requiring significant program modifications. The most appropriate device may be selected according to the required processing time of the control signal and of the application. A relevant case study is used to exemplify the procedure

Tuning of Ball and Beam System using Cascade Control

This project presents a new strategy to approach cascade control tuning by using image processing and machine learning to generate required control parameters to be set into the controller. For test bed purpose a ball balance upon a horizontal beam is used which is actuated with a stepper motor, angle of the balance to be scanned by a camera and analyzed using python alongside an ultrasonic sensor to measure real time distance to the ball, set point to be set by user and control action generated upon generating required information from hardware frame

Design and Implementation of Temperature Control for a Mini-chamber using Self-Tuning PID Controller

Despite its popularity in industrial application, PID controller suffers parameters setting difficulty due to set point change, disturbance, and ageing. This paper proposed Self-tuning PID controller using Dahlin method for temperature control of a laboratory scale mini-chamber. Experimental results show that the proposed controller has better performance compared to the conventional PID controller in term of rise time and settling time. It also shows that the algorithm can compensate the changing environment and robust toward the existence of disturbance

A Portable Implementation on Industrial Devices of a Predictive Controller Using Graphical Programming

This paper presents an approach for developing an Extended Prediction Self-Adaptive Controller employing graphical programming of industrial standard devices, for controlling fast processes. For comparison purposes, the algorithm has been implemented on three different FPGA (Field Programmable Gate Arrays) chips. The paper presents research aspects regarding graphical programming controller design, showing that a single advanced control application can run on different targets without requiring significant program modifications. Based on the time needed for processing the control signal and on the application, one can efficiently and easily select the most appropriate device. To exemplify the procedure, a conclusive case study is presented