Advances in PID Control

Since the foundation and up to the current state-of-the-art in control engineering, the problems of PID control steadily attract great attention of numerous researchers and remain inexhaustible source of new ideas for process of control system design and industrial applications. PID control effectiveness is usually caused by the nature of dynamical processes, conditioned that the majority of the industrial dynamical processes are well described by simple dynamic model of the first or second order. The efficacy of PID controllers vastly falls in case of complicated dynamics, nonlinearities, and varying parameters of the plant. This gives a pulse to further researches in the field of PID control. Consequently, the problems of advanced PID control system design methodologies, rules of adaptive PID control, self-tuning procedures, and particularly robustness and transient performance for nonlinear systems, still remain as the areas of the lively interests for many scientists and researchers at the present time. The recent research results presented in this book provide new ideas for improved performance of PID control applications

Industrial Applications: New Solutions for the New Era

This book reprints articles from the Special Issue "Industrial Applications: New Solutions for the New Age" published online in the open-access journal Machines (ISSN 2075-1702). This book consists of twelve published articles. This special edition belongs to the "Mechatronic and Intelligent Machines" section

High efficiency smart voltage regulating module for green mobile computing

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.In this thesis a design for a smart high efficiency voltage regulating module capable of supplying the core of modern microprocessors incorporating dynamic voltage and frequency scaling (DVS) capability is accomplished using a RISC based microcontroller to facilitate all the functions required to control, protect, and supply the core with the required variable operating voltage as set by the DVS management system. Normally voltage regulating modules provide maximum power efficiency at designed peak load, and the efficiency falls off as the load moves towards lesser values. A mathematical model has been derived for the main converter and small signal analysis has been performed in order to determine system operation stability and select a control scheme that would improve converter operation response to transients and not requiring intense computational power to realize. A Simulation model was built using Matlab/Simulink and after experimenting with tuned PID controller and fuzzy logic controllers, a simple fuzzy logic control scheme was selected to control the pulse width modulated converter and several methods were devised to reduce the requirements for computational power making the whole system operation realizable using a low power RISC based microcontroller. The same microcontroller provides circuit adaptations operation in addition to providing protection to load in terms of over voltage and over current protection. A novel circuit technique and operation control scheme enables the designed module to selectively change some of the circuit elements in the main pulse width modulated buck converter so as to improve efficiency over a wider range of loads. In case of very light loads as the case when the device goes into standby, sleep or hibernation mode, a secondary converter starts operating and the main converter stops. The secondary converter adapts a different operation scheme using switched capacitor technique which provides high efficiency at low load currents. A fuzzy logic control scheme was chosen for the main converter for its lighter computational power requirement promoting implementation using ultra low power embedded controllers. Passive and active components were carefully selected to augment operational efficiency. These aspects enabled the designed voltage regulating module to operate with efficiency improvement in off peak load region in the range of 3% to 5%. At low loads as the case when the computer system goes to standby or sleep mode, the efficiency improvent is better than 13% which will have noticeable contribution in extending battery run time thus contributing to lowering the carbon footprint of human consumption

Applications of neural networks to control systems

Tese de dout., Engenharia Electrónica, School of Electronic Engineering Science, Univ. of Wales, Bangor, 1992This work investigates the applicability of artificial neural networks to control systems. The following properties of neural networks are identified as of major interest to this field: their ability to implement nonlinear mappings, their massively parallel structure and their capacity to adapt. Exploiting the first feature, a new method is proposed for PID autotuning. Based on integral measures of the open or closed loop step response, multilayer perceptrons (MLPs) are used to supply PID parameter values to a standard PID controller. Before being used on-line, the MLPs are trained offline, to provide PID parameter values based on integral performance criteria. Off-line simulations, where a plant with time-varying parameters and time varying transfer function is considered, show that well damped responses are obtained. The neural PID autotuner is subsequently implemented in real-time. Extensive experimentation confirms the good results obtained in the off-line simulations. To reduce the training time incurred when using the error back-propagation algorithm, three possibilities are investigated. A comparative study of higherorder methods of optimization identifies the Levenberg-Marquardt (LM)algorithm as the best method. When used for function approximation purposes, the neurons in the output layer of the MLPs have a linear activation function. Exploiting this linearity, the standard training criterion can be replaced by a new, yet equivalent, criterion. Using the LM algorithm to minimize this new criterion, together with an alternative form of Jacobian matrix, a new learning algorithm is obtained. This algorithm is subsequently parallelized. Its main blocks of computation are identified, separately parallelized, and finally connected together. The training time of MLPs is reduced by a factor greater than 70 executing the new learning algorithm on 7 Inmos transputers

A Framework for Automatic Dynamic Constraint Verification in Cyber Physical System Modeling Languages

Design of Cyber-Physical Systems (CPSs) involves overlapping the domains of control theory, network communication, and computational algorithms. Involving multiple domains within the same design greatly increases the system complexity. Furthermore, the physical nature of CPSs generally involves important safety constraints where constraint violations can be catastrophic. The design of CPSs benefits from focusing on the construction of abstracted, high-level models in a DomainSpecific Modeling Language (DSML). A Domain-Specific Modeling Environment (DSME) may aid in the design of such complex systems by enforcing structural design constraints during the construction of models. Models built using a DSME may also use compilers or interpreters to produce real working, low-level artifacts that represent the high-level design. Though each model in a DSME may abide by a formal specification, the behavior of a design may violate dynamic constraints if deployed. Engineers are tasked to ensure that models behave safely by implementing their expert knowledge after using appropriate verification tools. Constraint violations may be eliminated by a modification of the model based on verification feedback, known as Dynamic Constraint Feedback (DCF). Mending such constraint violations is a task generally performed by the model designer. Such a process could potentially be automated through the capture of well-known design practices. The challenging task when automating model correction then becomes in the design of a DSML. A designer of a DSML may have a clear understanding of how to design the syntax and semantics for their domain, but there are no formal methods for implementing verification tools for automatic model correction. Such a framework could greatly aid in the selection of available verification tools, implement well-established design methods, and model dynamic constraints. Presented is the Dynamic Constraint Feedback Metamodeling Language (DCFML), a new metamodel to implement DCF upfront in DSML design. This particular solution provides a concrete solution to the abstraction of the various components of DCF, and then appends them to the DSML design process provided by a DSME

A PLC-based Hybrid Fuzzy PID Controller for PWM-driven Variable Speed Drive

In adjustable-speed drive applications, the range of speed and torque achievable is very important. A power electronic converter is needed as an interface between the input AC power and the drive. A controller is needed to make the motor (drive), through the power electronics converter meets the drive requirements. The widely used conventional control that is based on mathematical model of the controlled system is very complex and not easy to be determined since it requires explicit knowledge of the motor and load dynamics. This thesis proposed a design and implementation of a PLC-based hybrid controller from a basic PLC to a PWM-driven variable-voltage variable-frequency (VVVF) speed control of an induction motor and the analysis, evaluation and improvement of the control strategies. A simulation model in MA TLAB/Simulink is developed using system identification technique to perform verification of the PLCbased intelligent controller of the PWM-driven VVVF algorithm. To provide stability in response to sudden changes in reference speed and/or load torque, a switching type controller consisting of two control modes are devised: a PID-type fuzzy controller consisting of a PI-type and a PD-type fuzzy controller, and a conventional PID. The proposed scenario is implementing a strategy when the actual value is closed to setpoint. At the early phase of the control action, the control task is handled by the PIDtype fuzzy controller. At a later phase when the absolute of error is less than a threshold value, the input of integrator at the output side is no longer given by fuzzy action but fed by the incremental PID action. In term of control action, this is an enhanced proportional and derivative action when the actual value is closed to reference. Detailed evaluations of the controller's performance based-on a predefined performance indices under several conditions are presented. The findings demonstrate the ability of the control approach to provide a viable control solution in response to the different operating conditions and requirements

A fluid power application of alternative robust control strategies

This thesis presents alternative methods for designing a speed controller for a hydrostatic power transmission system. Recognising that such a system, comprising a valve controlled motor supplied by the laboratory ring main and driving a hydraulic pump as a load, contains significant non-linearities, the thesis shows that robust 'modern control' approaches may be applied to produce viable controllers without recourse to the use of a detailed model of the system. In its introduction, it considers why similar approaches to the design of fluid power systems have not been applied hitherto. It then sets out the design and test, in simulation and on a physical rig, of two alternative linear controllers using H∞ based methods and a 'self organising fuzzy logic' controller (SOFLC). In the linear approaches, differences between the characteristics of the system and the simple models of it are accommodated in the controller design route as 'perturbations' or 'uncertainties'. The H∞ based optimisation methods allow these to be recognised in the design. “Mixed sensitivity” and “Loop shaping” methods are each applied to design controllers which are tested successfully on the laboratory rig. The SOFLC in operation does not rely on a model, but instead allows fuzzy control rules to evolve. In the practical tests, the system is subjected to a range of disturbances in the form of supply pressure fluctuations and load torque changes. Also presented are test results for proportional and proportional plus integral (PI) controllers, to provide a reference. It is demonstrated qualitatively that performance using the linear controllers is superior to that using proportional and PI controllers. An increased range of stable operation is achieved by the controller designed using “loop shaping” – performance is enhanced by the use of two controllers selected automatically according to the operating speed, using a “bumpless” transfer routine. The SOFLC proved difficult to tune. However, stable operation was achieved.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Advances in Condition Monitoring, Optimization and Control for Complex Industrial Processes

The book documents 25 papers collected from the Special Issue “Advances in Condition Monitoring, Optimization and Control for Complex Industrial Processes”, highlighting recent research trends in complex industrial processes. The book aims to stimulate the research field and be of benefit to readers from both academic institutes and industrial sectors