Optimum Weight Selection Based LQR Formulation for the Design of Fractional Order PI{\lambda}D{\mu} Controllers to Handle a Class of Fractional Order Systems

A weighted summation of Integral of Time Multiplied Absolute Error (ITAE) and Integral of Squared Controller Output (ISCO) minimization based time domain optimal tuning of fractional-order (FO) PID or PI{\lambda}D{\mu} controller is proposed in this paper with a Linear Quadratic Regulator (LQR) based technique that minimizes the change in trajectories of the state variables and the control signal. A class of fractional order systems having single non-integer order element which show highly sluggish and oscillatory open loop responses have been tuned with an LQR based FOPID controller. The proposed controller design methodology is compared with the existing time domain optimal tuning techniques with respect to change in the trajectory of state variables, tracking performance for change in set-point, magnitude of control signal and also the capability of load disturbance suppression. A real coded genetic algorithm (GA) has been used for the optimal choice of weighting matrices while designing the quadratic regulator by minimizing the time domain integral performance index. Credible simulation studies have been presented to justify the proposition.Comment: 6 pages, 5 figure

Sviluppo di tecniche di monitoraggio delle prestazioni di processi chimici controllati

La tesi proposta tratta del monitoraggio delle prestazioni dei controllori in processi chimici. Diverse sono le cause di malfunzionamento: da valvole con attrito, a regolatori sintonizzati impropriamente alla propagazione di disturbi negli impianti. Con questa tesi si vuole illustrare una metodologia per individuare le cause di mancata prestazione in modo da poterle classificare ed intraprendere le necessarie contromisure. In particolare é stato approfondito il problema della sintonizzazione dei regolatori ed è stata proposta una tecnica di identificazione basata sullo studio dei disturbi, evitando quindi ulteriori sollecitazioni agli impianti per variazioni di set-point. Inoltre è stato affrontato il problema dell’attrito sulle valvole utilizzando diverse tecniche di individuazione automatica originali e già presentetate in letteratura. Il tutto è stato organizzato in un software sviluppato in ambiente Matlab

Optimum Weight Selection Based LQR Formulation for the Design of Fractional Order PIλDμ Controllers to Handle a Class of Fractional Order Systems

This is the author accepted manuscript. The final version is available from IEEE via the DOI in this record.A weighted summation of Integral of Time Multiplied Absolute Error (ITAE) and Integral of Squared Controller Output (ISCO) minimization based time domain optimal tuning of fractional-order (FO) PID or PI{\lambda}D{\mu} controller is proposed in this paper with a Linear Quadratic Regulator (LQR) based technique that minimizes the change in trajectories of the state variables and the control signal. A class of fractional order systems having single non-integer order element which show highly sluggish and oscillatory open loop responses have been tuned with an LQR based FOPID controller. The proposed controller design methodology is compared with the existing time domain optimal tuning techniques with respect to change in the trajectory of state variables, tracking performance for change in set-point, magnitude of control signal and also the capability of load disturbance suppression. A real coded genetic algorithm (GA) has been used for the optimal choice of weighting matrices while designing the quadratic regulator by minimizing the time domain integral performance index. Credible simulation studies have been presented to justify the proposition

Life buoy

A lifebuoy such as figure 1, or we can call as ring buoy, lifering, lifesaver, life donut, life preserver or lifebelt, also known as a "perry buoy", or "kisby ring". The "kisby ring", or sometimes will be call "Kisbie ring", is thought to be named after Thomas Kisbee (1792–1877) who was a British naval officer. Lifebuoy is a lifesaving buoy designed to save someone in the water. It also can provide buoyancy and prevent drowning. To improve aid rescue at night, mostly lifebuoys are fitted with one or more seawater-activated lights

Fuzzy Logic for pH Neutralization Process

pH neutralization process is a process that is widely studied due to its highly nonlinear process reaction. Its nonlinearity behavior is caused by static nonlinearity between pH and concentration. This nonlinearity depends on the substances in the solution and on their concentrations. In this project, the nonlinearity of the process was investigated. Later, the mathematical model of the process was developed based on McAvoy et al [I]. In addition to the mathematical model, an empirical model was also obtained from Analytical & Chemical Pilot Plant located in the Process Control & Instrumentation Laboratory (23-00-06). Both models were then used to develop the Fuzzy Logic Controller (FLC) by using Advanced-Neuro Fuzzy Inference System (ANFIS) and also gain-scheduling method. In ANFIS implementation for empirical model, the FLC output was identical to the output from PID. Therefore it is concluded that FLC could be used to replace PID for empirical model. In ANFIS implementation for mathematical model, the FLC also could be implemented for mathematical model since the controlled variable successfully follows all the set point changes. For gainscheduling method, the FLC was tested on servo and regulator problems. The servo test was performed by using a random number generator to generate random pH set points between 3 and 11 and the simulation is performed for 100 seconds. The result for the servo test was similar with the result from the ANFIS implementation for mathematical model. For regulator test, the disturbance was the ±20% variation in acid flow. The result for the regulator shows, the controller manages to eliminate the disturbance effect in the process variable. In overall, the project successfully shows that FLC could be a good alternative to PID controller

Flight desk control demonstrator

The aim of a control system is to obtain a desired output response according to an input command. This can be achieved by knowing a model of the system with an open-loop control. However, an accurate model can be difficult to obtain. With a closed-loop control system, the controller determines the input signal of the process by using the measurement of the output. The most used method in the industry world involves PID correction. The concept of feedback control and the choice of the three gains (Proportional, Integrator, Derivative) for a simple PID controller can be quite hard for students to conceptualize and understand their effectiveness. The aim of this project is to develop a simple feedback system for aerospace students to understand the nature of feedback control, the choice and the influence of the PID terms. The system consists of a demonstrator for the control of the pitch angle of a simple aerofoil by means of a regulated flap. This document focuses on the process to design a fully working demonstrator including the design of the demonstrator, its building and the programming of the GUI (Graphical User Interface). The first step is to create an aerodynamic model of the system. Once a reliable model is obtained, a structural layout is suggested, based on existing wind tunnel design. The wind tunnel design is critical because the geometry has a direct impact on the loads acting on the aerofoil and it must satisfy aerodynamic requirements. The wind tunnel must create favourable aerodynamic conditions to make an easier control of the aerofoil by its flap. Then, the demonstrator is built using laser cutting and 3D printing. The PID controller is implemented into an Arduino board programmed in C++ connected via Bluetooth to the GUI on a computer programmed in JAVA. It is possible to plot and save the output of the demonstrator as well as send new settings to the controller. The demonstrator will be assessed, and several PID settings are suggested