Analysis of Transient Response for Coupled Tank System via Conventional and Particle Swarm Optimization (PSO) Techniques

This paper investigates the implementation of conventional and Particle Swarm Optimization (PSO) techniques to obtain optimal parameters of controller. In this research, the transient responses of the Coupled Tank System (CTS) are analyzed with the various conventional and metaheuristic techniques which are Trial and Error, Auto-Tuning, Ziegler-Nichols (ZN), Cohen-Coon (CC), standard PSO and Priority-based Fitness PSO (PFPSO) to tune the PID controller parameters. The purpose of this research is to maintain the liquid at the specific or required height in the tank. Simulation is conducted within Matlab environment to verify the performance of the system in terms of Settling Time (Ts), Steady State Error (SSE) and Overshoot (OS). It has been demonstrated that implementation of meta-heuristic techniques are potential approach to control the desired liquid level and improve the system performances

Non-overshooting PD and PID controllers design

This paper involves the design of non-overshooting PD and PID controllers for some special plants. The PID controller parameters are determined to reach a stable closed-loop system with monotonically decreasing frequency response. Thus specific regions in the controller parameters space are obtained. Gain crossover frequency and phase isodamping property are employed to choose an appropriate solution among the obtained solutions. The performance of the proposed PD and PID controllers in position and velocity control of a laboratory DC servomechanism system is investigated through experimental tests

Practical modelling and control implementation studies on a pH neutralization process pilot plant

In recent years the industrial application of advanced control techniques for the process industries has become more demanding, mainly due to the increasing complexity of the processes themselves as well as to enhanced requirements in terms of product quality and environmental factors. Therefore the process industries require more reliable, accurate, robust, efficient and flexible control systems for the operation of process plant. In order to fulfil the above requirements there is a continuing need for research on improved forms of control. There is also a need, for a variety of purposes including control system design, for improved process models to represent the types of plant commonly used in industry. Advanced technology has had a significant impact on industrial control engineering. The new trend in terms of advanced control technology is increasingly towards the use of a control approach known as an “intelligent” control strategy. Intelligent control can be described as a control approach or solution that tries to imitate important characteristics of the human way of thinking, especially in terms of decision making processes and uncertainty. It is also a term that is commonly used to describe most forms of control systems that are based on artificial neural networks or fuzzy logic. The first aspect of the research described in the thesis concerns the development of a mathematical model of a specific chemical process, a pH neutralization process. It was intended that this model would then provide an opportunity for the development, implementation, testing and evaluation of an advanced form of controller. It was also intended that this controller should be consistent in form with the generally accepted definition of an “intelligent” controller. The research has been based entirely around a specific pH neutralization process pilot plant installed at the University Teknologi Petronas, in Malaysia. The main feature of interest in this pilot plant is that it was built using instrumentation and actuators that are currently used in the process industries. The dynamic model of the pilot plant has been compared in detail with the results of experiments on the plant itself and the model has been assessed in terms of its suitability for the intended control system design application. The second stage of this research concerns the implementation and testing of advanced forms of controller on the pH neutralization pilot plant. The research was also concerned with the feasibility of using a feedback/feedforward control structure for the pH neutralization process application. Thus the study has utilised this control scheme as a backbone of the overall control structure. The main advantage of this structure is that it provides two important control actions, with the feedback control scheme reacting to unmeasured disturbances and the feedforward control scheme reacting immediately to any measured disturbance and set-point changes. A non-model-based form of controller algorithm involving fuzzy logic has been developed within the context of this combined feedforward and feedback control structure. The fuzzy logic controller with the feedback/feedforward control approach was implemented and a wide range of tests and experiments were carried out successfully on the pilot plant with this type of controller installed. Results from this feedback/feedforward control structure are extremely encouraging and the controlled responses of the plant with the fuzzy logic controller show interesting characteristics. Results obtained from tests of these closed-loop system configurations involving the real pilot plant are broadly similar to results found using computer-based simulation. Due to limitations in terms of access to the pilot plant the investigation of the feedback/feedforward control scheme with other type of controllers such as Proportional plus Integral (PI) controller could not be implemented. However, extensive computer-based simulation work was carried out using the same control scheme with PI controller and the control performances are also encouraging. The emphasis on implementation of advanced forms of control with a feedback/feedforward control scheme and the use of the pilot plant in these investigations are important aspects of the work and it is hoped that the favourable outcome of this research activity may contribute in some way to reducing the gap between theory and practice in the process control field

Engine Data Interpretation System (EDIS), phase 2

A prototype of an expert system was developed which applies qualitative constraint-based reasoning to the task of post-test analysis of data resulting from a rocket engine firing. Data anomalies are detected and corresponding faults are diagnosed. Engine behavior is reconstructed using measured data and knowledge about engine behavior. Knowledge about common faults guides but does not restrict the search for the best explanation in terms of hypothesized faults. The system contains domain knowledge about the behavior of common rocket engine components and was configured for use with the Space Shuttle Main Engine (SSME). A graphical user interface allows an expert user to intimately interact with the system during diagnosis. The system was applied to data taken during actual SSME tests where data anomalies were observed

PID CONTROL DESIGN WITH DECOUPLING ON LEVEL COUPLED TANK CONTROL SYSTEM

Masalah pada Level Coupled Tank adalah adanya gangguan dalam aliran yang memasok tank akan membuat respon ketidakstabilan, sehingga bisa terjadi interaksi silang antara masukan dan keluaran. Kontrol PI adalah pilihan yang menarik ketika perumusan metode yang diusulkan untuk sistem Coupled Tank TITO. Kontrol PI memiliki kemampuan untuk mempertahankan nilai steady state pada respon gangguan. Dalam penelitian ini, menggunakan Decoupling dalam proses interaksi silang untuk setiap tangki. Coupled Tank pada sistem TITO dapat diubah fungsi transfernya ke SISO, sehingga dapat meminimalkan efek interaksi. Cara yang baik untuk merancang model adalah mempertimbangkan keadaan pada plant itu, jadi model kontrol yang diinginkan mampu mengatasi ketidak-linearitas dari sistem TITO. Simulasi menunjukkan nilai persen overshoot (Mp), settling time (Ts) dan error steady state (Ess), dari state pada masing-masing sistem adalah 0%, 38 detik, dan 0,22%.The problems on the Coupled Tank control level is the existence of disturbance in the flow that supplies tank would make unstability response, so it could happen the cross interaction between input and output. PI control is an attractive option when the formulation of the proposed method to the Coupled Tank TITO system. PI control has the ability to maintain a steady state value of the response of the disturbance. In this study, it use Decoupling in cross interaction processes for every tank. Coupled Tank on TITO system can changes transfer function to SISO, so it can minimize the effect of interactions. The good way to design a model is consider the state on that plant, so the desired control model capable save non-linearity from TITO system. The simulations show value of percent overshoot (Mp), settling time (Ts) and steady state error (Ess), of the state of each system was 0%, 38 seconds, and 0.22%

IMPLEMENTATION OF FEEDFORWARD AND PID CONTROL STRATEGIES ON CONTROL LOOP FIELDBUS FOUNDATION PROTOCOL

This report is intended to discuss the project undertaken to design, analyse and fabricate a simple control loop using a fieldbus foundation protocol. The first control systems used mechanical and pneumatic controllers and were designed merely to achieve stability rather than economic performance. Later in the 1970s, distributed control system (DCS) emerged to replace the conventional technology. In DCS, a central processor controls all parameters however, it has limitation in term of reliability, robustness and cost. This lead to the introduction of network communication for industrial process known as the fieldbus system replacing the DCS architecture by enabling distribution of control function to equipment in the field such as sensors, controllers and actuators. In this project configuration and implementation procedure for the development of fieldbus process loop is presented involving three process variables that are the temperature, pressure and level together with PID and feedforward control strategies. The methodology towards accomplishing the project includes the theoretical and technical research, the installation and commissioning, the configuration network of fieldbus protocol together with HART protocol, the troubleshooting, operation and maintenance, and the analysis of the fieldbus advantages and benefits. The findings demonstrates the benefits of the fieldbus system in term of cost saving, data quality and quantity, simpler and better controllability

NON-LINEAR MODEL PREDICTIVE CONTROL STRATEGIES FOR PROCESS PLANTS USING SOFT COMPUTING APPROACHES

The developments of advanced non-linear control strategies have attracted a considerable research interests over the past decades especially in process control. Rather than an absolute reliance on mathematical models of process plants which often brings discrepancies especially owing to design errors and equipment degradation, non-linear models are however required because they provide improved prediction capabilities but they are very difficult to derive. In addition, the derivation of the global optimal solution gets more difficult especially when multivariable and non-linear systems are involved. Hence, this research investigates soft computing techniques for the implementation of a novel real time constrained non-linear model predictive controller (NMPC). The time-frequency localisation characteristics of wavelet neural network (WNN) were utilised for the non-linear models design using system identification approach from experimental data and improve upon the conventional artificial neural network (ANN) which is prone to low convergence rate and the difficulties in locating the global minimum point during training process. Salient features of particle swarm optimisation and a genetic algorithm (GA) were combined to optimise the network weights. Real time optimisation occurring at every sampling instant is achieved using a GA to deliver results both in simulations and real time implementation on coupled tank systems with further extension to a complex quadruple tank process in simulations. The results show the superiority of the novel WNN-NMPC approach in terms of the average controller energy and mean squared error over the conventional ANN-NMPC strategies and PID control strategy for both SISO and MIMO systemsPetroleum Training Development Fun

Development of the Web-based control laboratory and long distance education.

Qu Cong.Thesis (M.Phil.)--Chinese University of Hong Kong, 2003.Includes bibliographical references (leaves i-iii (3rd gp.)).Abstracts in English and Chinese.Acknowledgements --- p.iContent --- p.iiAbstract --- p.ivAbstract (Chinese) --- p.viChapter Chapter 1 --- Introduction --- p.1Chapter 1.1 --- Long Distance Laboratory --- p.1Chapter 1.2 --- Overview of Web-Based Laboratory --- p.3Chapter 1.3 --- Project of Development of Web-Based Laboratory --- p.5Chapter 1.4 --- Thesis Outline --- p.7Chapter Chapter 2 --- Laboratory Layout --- p.8Chapter 2.1 --- DC Motor System --- p.9Chapter 2.2 --- Coupled Tank System --- p.11Chapter 2.3 --- Mass-Spring-Damper System --- p.13Chapter 2.4 --- Ball and Beam System --- p.15Chapter 2.5 --- Configurations --- p.16Chapter Chapter 3 --- System Architecture --- p.18Chapter 3.1 --- Hardware Architecture --- p.18Chapter 3.2 --- Software Architecture --- p.21Chapter 3.3 --- Architecture Characteristics --- p.24Chapter Chapter 4 --- Control Methodology --- p.28Chapter 4.1 --- Basic Control Concepts --- p.28Chapter 4.2 --- System Modeling --- p.30Chapter 4.3 --- Controller Design Methods --- p.36Chapter 4.4 --- Digital Control --- p.42Chapter Chapter 5 --- Mass-Spring-Damper System --- p.45Chapter 5.1 --- System Setup --- p.45Chapter 5.2 --- Experiment Design --- p.49Chapter Chapter 6 --- Ball and Beam System --- p.58Chapter 6.1 --- System Setup --- p.59Chapter 6.2 --- Experiment Design --- p.61Chapter Chapter 7 --- Education Practice --- p.76Chapter 7.1 --- Practice and Analysis --- p.76Chapter 7.2 --- Remarks --- p.80Chapter Chapter 8 --- Conclusions and Future Work --- p.82Chapter 8.1 --- Concluding Remarks --- p.82Chapter 8.2 --- Future Work --- p.84Bibliography --- p.

Automation of closed environments in space for human comfort and safety

This report culminates the work accomplished during a three year design project on the automation of an Environmental Control and Life Support System (ECLSS) suitable for space travel and colonization. The system would provide a comfortable living environment in space that is fully functional with limited human supervision. A completely automated ECLSS would increase astronaut productivity while contributing to their safety and comfort. The first section of this report, section 1.0, briefly explains the project, its goals, and the scheduling used by the team in meeting these goals. Section 2.0 presents an in-depth look at each of the component subsystems. Each subsection describes the mathematical modeling and computer simulation used to represent that portion of the system. The individual models have been integrated into a complete computer simulation of the CO2 removal process. In section 3.0, the two simulation control schemes are described. The classical control approach uses traditional methods to control the mechanical equipment. The expert control system uses fuzzy logic and artificial intelligence to control the system. By integrating the two control systems with the mathematical computer simulation, the effectiveness of the two schemes can be compared. The results are then used as proof of concept in considering new control schemes for the entire ECLSS. Section 4.0 covers the results and trends observed when the model was subjected to different test situations. These results provide insight into the operating procedures of the model and the different control schemes. The appendix, section 5.0, contains summaries of lectures presented during the past year, homework assignments, and the completed source code used for the computer simulation and control system

Comparative Study for Controller Design of Time-delay Systems

Time delays are usually unavoidable in many mechanical and electrical systems. The presence of delay typically imposes strict limitations on achievable feedback performance in both continuous and discrete systems. The presence of the delay complicates the design process as it makes continuous systems to be infinite dimensional and it significantly increases the dimensions in discrete systems. Most of classical methods used controller design cannot be used with delayed systems. In this study, the delay will be modeled using different approaches such as Pad’e approximation and Smith Predictor in continuous system and modified z-transform in discreet systems. In this study, the delays are assumed to be constant and known. The delays in the system are lumped in the plant model. This study will show the design of stable and optimal controller for time-delay systems using algebraic Riccati equation solutions and PID control. This study will also present comparison between these controllers