Showing papers on "Control theory published in 1995"

The unified power flow controller: a new approach to power transmission control

Abstract: This paper shows that the unified power flow controller (UPFC) is able to control both the transmitted real power and, independently, the reactive power flows at the sending- and the receiving-end of the transmission line. The unique capabilities of the UPFC in multiple line compensation are integrated into a generalized power flow controller that is able to maintain prescribed, and independently controllable, real power and reactive power flow in the line. The paper describes the basic concepts of the proposed generalized P and Q controller and compares it to the more conventional, but related power flow controllers, such as the thyristor-controlled series capacitor and thyristor-controlled phase angle regulator. The paper also presents results of computer simulations showing the performance of the UPFC under different system conditions. >

Control of a nonholonomic mobile robot: backstepping kinematics into dynamics

Abstract: A dynamical extension that makes possible the integration of a kinematic controller and a torque controller for nonholonomic mobile robots is presented. A combined kinematic/torque control law is developed using backstepping and asymptotic stability is guaranteed by Lyapunov theory. Moreover, this control algorithm can be applied to the three basic nonholonomic navigation problems: tracking a reference trajectory, path following and stabilization about a desired posture. A general structure for controlling a mobile robot results that can accommodate different control techniques ranging from a conventional computed-torque controller, when all dynamics are known, to adaptive controllers.

Optimal Control Theory for Infinite Dimensional Systems

Abstract: In each time domain, LTR is described in three chapters, organized as: preliminary analysis, detailed analysis, and design. The two chapters on preliminary analysis deal mainly with controller structures, i.e., especially with observer architectures. It is demonstrated how different observer architectures have different advantages and drawbacks. It turns out that the recovery properties of the various controller types all can be characterized in terms of a certain matrix valued function, the recovery matrix. Different variations of the recovery problem are then restated in terms of the recovery matrix. In the two chapters containing a detailed analysis, LTR is investigated by means of the special coordinate basis. The analysis is quite insightful and sheds light on a variety of related problems also. In this context the authors introduce a new concept, recovery in subspaces, where the idea basically is to extract for a given system the properties that actually can be recovered and then concentrate upon these. The chapters dealing with synthesis characterize the degrees of freedom involved with recovery design. Explicit design methods include: eigenstructure assignment, and optimization, and subspace recovery design. Also, both for the continuous and for the discrete-time case, closed-loop recovery is discussed. Historically, LTR was formulated as open-loop problems, but obviously, if the design objective is a concrete, closed-loop property, it is more natural to pose the whole problem in a closed-loop formulation. The treatment and the applied methods are in form and spirit similar to the open-loop results. The final chapter of the book discusses controller architecture in the light of the design problems that have been given treatment in the preceding chapters. As a main point here is the introduction of the so-called CSS architecture (the acronym is formed by the initials of the authors). It is demonstrated that in most cases this controller architecture does significantly better than the classical architectures. One problem, though, is that a CSS controller by construction is internally stable. Since there exist a class of unstable systems that can be stabilized only by unstable controllers, the CSS controllers do not apply always. The CSS architecture is formulated both in terms of full-order and reducedorder controllers. Since Loop Transfer Recovery: Analysis and Designis the first book dedicated to this subject, it is not directly comparable with other monographs. It does, however, in an elegant way combine the tradition from classical monographs on observer theory [6], on loopshaping [7], and on geometric methods [8]. In comparison to these references Loop Transfer Recovery: Analysis and Design offers a broader and more unified approach to multivariable control synthesis.

Simultaneous design of membership functions and rule sets for fuzzy controllers using genetic algorithms

Abstract: This paper examines the applicability of genetic algorithms (GA's) in the simultaneous design of membership functions and rule sets for fuzzy logic controllers. Previous work using genetic algorithms has focused on the development of rule sets or high performance membership functions; however, the interdependence between these two components suggests a simultaneous design procedure would be a more appropriate methodology. When GA's have been used to develop both, it has been done serially, e.g., design the membership functions and then use them in the design of the rule set. This, however, means that the membership functions were optimized for the initial rule set and not the rule set designed subsequently. GA's are fully capable of creating complete fuzzy controllers given the equations of motion of the system, eliminating the need for human input in the design loop. This new method has been applied to two problems, a cart controller and a truck controller. Beyond the development of these controllers, we also examine the design of a robust controller for the cart problem and its ability to overcome faulty rules. >

Adaptive control of plants with unknown hystereses

Abstract: For a system with hysteresis, the authors present a parameterized hysteresis model and develop a hysteresis inverse. The authors then design adaptive controllers with an adaptive hysteresis inverse for plants with unknown hysteresis. A new adaptive controller structure is introduced which is capable of achieving a linear parameterization and a linear error model in the presence of a hysteresis nonlinearity. A robust adaptive law is used to update the controller parameters and hysteresis inverse parameters, which ensures the global boundedness of the closed-loop signals for a wide class of of hysteresis models. Simulations show that the use of the adaptive hysteresis inverse leads to major improvements of system performance. >

Neural net robot controller with guaranteed tracking performance

Abstract: A neural net (NN) controller for a general serial-link robot arm is developed. The NN has two layers so that linearity in the parameters holds, but the "net functional reconstruction error" and robot disturbance input are taken as nonzero. The structure of the NN controller is derived using a filtered error/passivity approach, leading to new NN passivity properties. Online weight tuning algorithms including a correction term to backpropagation, plus an added robustifying signal, guarantee tracking as well as bounded NN weights. The NN controller structure has an outer tracking loop so that the NN weights are conveniently initialized at zero, with learning occurring online in real-time. It is shown that standard backpropagation, when used for real-time closed-loop control, can yield unbounded NN weights if (1) the net cannot exactly reconstruct a certain required control function or (2) there are bounded unknown disturbances in the robot dynamics. The role of persistency of excitation is explored. >

Nonlinear adaptive control of active suspensions

Abstract: In this paper, a previously developed nonlinear "sliding" control law is applied to an electro-hydraulic suspension system. The controller relies on an accurate model of the suspension system. To reduce the error in the model, a standard parameter adaptation scheme, based on Lyapunov analysis, is introduced. A modified adaptation scheme, which enables the identification of parameters whose values change with regions of the state space, is then presented. These parameters are not restricted to being slowly time-varying as in the standard adaptation scheme; however, they are restricted to being constant or slowly time varying within regions of the state space. The adaptation algorithms are coupled with the control algorithm and the resulting system performance is analyzed experimentally. The performance is determined by the ability of the actuator output to track a specified force. The performance of the active system, with and without the adaptation, is analyzed. Simulation and experimental results show that the active system is better than a passive system in terms of improving the ride quality of the vehicle. Furthermore, both of the adaptive schemes improve performance, with the modified scheme giving the greater improvement in performance. >

Fuzzy logic based intelligent control of a variable speed cage machine wind generation system

Abstract: The paper describes a variable speed wind generation system where fuzzy logic principles are used for efficiency optimization and performance enhancement control. A squirrel cage induction generator feeds the power to a double-sided pulse width modulated converter system which pumps power to a utility grid or can supply to an autonomous system. The generation system has fuzzy logic control with vector control in the inner loops. A fuzzy controller tracks the generator speed with the wind velocity to extract the maximum power. A second fuzzy controller programs the machine flux for light load efficiency improvement, and a third fuzzy controller gives robust speed control against wind gust and turbine oscillatory torque. The complete control system has been developed, analyzed, and validated by simulation study. Performances have then been evaluated in detail.

Adaptation and learning using multiple models, switching, and tuning

Abstract: This article presents a general methodology for the design of adaptive control systems which can learn to operate efficiently in dynamical environments possessing a high degree of uncertainty. Multiple models are used to describe the different environments and the control is effected by switching to an appropriate controller followed by tuning or adaptation. The study of linear systems provides the theoretical foundation for the approach and is described first. The manner in which such concepts can be extended to the control of nonlinear systems using neural networks is considered next. Towards the end of the article, the applications of the above methodology to practical robotic manipulator control is described. >

Optimum aerodynamic design using CFD and control theory

Abstract: Optimum Aerodynamic Design Using CFD and Control Theory

Concepts for design of FACTS controllers to damp power swings

Abstract: The design of controllers sited in the transmission network for damping interarea power oscillations requires several types of analytical tools and field verification methods. Probably the most important aspect of such control design is the selection of proper feedback measurements from the network. This paper describes concepts which provide design engineers with the insight to control performance and the understanding needed to ensure the secure operation of the bulk transmission system. Specific attention is directed to procedures for selecting feedback signals. >

Bilateral controller for teleoperators with time delay via /spl mu/-synthesis

Abstract: In the standard teleoperator system, force and velocity signals are communicated between a master robot and a slave robot. It is well known that the system can become unstable when even a small time delay exists in the communication channel. In this paper, a method based on the /spl Hscr//sub /spl infin//-optimal control and /spl mu/-synthesis frameworks is introduced to design a controller for the teleoperator that achieves stability for a prespecified time-delay margin while optimizing performance specifications. A numerical design example is included. >

Adaptive nonlinear design with controller-identifier separation and swapping

Abstract: We present a new adaptive nonlinear control design which achieves a complete controller-identifier separation. This modularity is made possible by a strong input-to-state stability property of the new controller with respect to the parameter estimation error and its derivative as inputs. These inputs are independently guaranteed to be bounded by the identifier. The new design is more flexible than the Lyapunov-based design because the identifier can employ any standard update law gradient and least-squares, normalized and unnormalized. A key ingredient in the identifier design and convergence analysis is a nonlinear extension of the well-known linear swapping lemma. >

Linked gaming machines having a common feature controller

Abstract: The preferred embodiment of the present invention operates on a system (100) of interconnected gaming machines (101-108) and selectively provides one or more active features to all of the gaming machines (101-108) linked to the system (100). The enablement of the feature may be based on the combined results from previous plays on the individual gaming machines (101-108). The feature may be a bonus award for a specific displayed combination, an increased possibility for a winning combination, or any other feature which alters the normal operation of the gaming machines (101-108). The first machine (101-108) to generate a winning game result to which the feature applies will be given an award based upon the feature. The feature is then disabled and the system returns to normal play mode until the feature is again enabled. Various other features are described.

Run by run process control: combining SPC and feedback control

Abstract: The run by run controller provides a framework for controlling a process which is subject to disturbances such as shifts and drifts as a normal part of its operation. The run by run controller combines the advantages of both statistical process control (SPC) and feedback control. It has three components: rapid mode, gradual mode, and generalized SPC. Rapid mode adapts to sudden shifts in the process such as those caused by maintenance operations. Gradual mode adapts to gradual drifts in the process such as those caused by build-up of deposition inside a reactor. The choice between the two modes is determined by the outcome from generalized SPC which allows SPC to be applied to a process while it is being tuned. The run by run controller has been applied to the control of a silicon epitaxy process in a barrel reactor. Rapid mode recovered the process within 3 runs after a disturbance. Gradual mode reduced the variation of the process by a factor of 2.7 as compared to historical data. >

Comparative study of proportional-integral, sliding mode and fuzzy logic controllers for power converters

Abstract: This paper presents a comparative evaluation of the proportional-integral, sliding mode and fuzzy logic controllers for applications to power converters. The mismatch between the characteristics which lead to varying performance is outlined. This paper also demonstrates certain similarities of both the fuzzy logic controller and sliding mode controller. Sensitivity of these controllers to supply voltage disturbances and load disturbances is studied and results are presented.

Families of Exponentials: The Method of Moments in Controllability Problems for Distributed Parameter Systems

Abstract: From the Publisher: This book presents the newly developed theory of non-harmonic Fourier series and its applications to the control of distributed parameter systems The book begins with the modern theory of exponentials, using an operator theory approach, then extends this to the method of moments--one of the most powerful tools in control theory Applications to various types of control problems are discussed Researchers in control theory, functional analysis, and partial differential equations will find much to interest them in this treatise

Synchronous frame based controller implementation for a hybrid series active filter system

Abstract: This paper proposes a synchronous reference frame based controller for a hybrid series active filter system. A hybrid series active filter system has been designed, built and installed at Beverly Pump Station in New England Electric utility for 765 kVA adjustable speed drive load to meet IEEE 519 recommended harmonic standards. The series active filter is rated 35 kVA-4% of the load kVA, and is controlled by a synchronous reference frame based controller to act as a harmonic isolator between the supply and load. This paper discusses the basic synchronous reference frame controller structure and addresses its operation under nonunity controller loop gain conditions. Design trade-offs and implementation issues of the synchronous reference frame controller are discussed. Operation of the hybrid series active filter system under off-tuned passive filter conditions and its impact on the performance of the synchronous reference frame based controller is experimentally evaluated. Effectiveness of the series active filter to provide harmonic damping and the use of simpler and low cost power factor correction capacitors as passive filters, is demonstrated by laboratory experimental results. Field installation and laboratory experimental results demonstrate the practical viability of the synchronous reference frame based controller for hybrid series active filter to provide harmonic isolation of nonlinear loads and to comply with IEEE 519 recommended harmonic standards.

Active control of sound and vibration

Abstract: In many industrial and defense applications noise and vibration are important problems. The conventional method of treatment is to use passive damping techniques or to redesign the system. However, passive damping techniques are primarily effective at higher frequencies, and redesign is often costly and ineffective. In the last decade, active control of sound and vibration (at audio frequencies) has emerged as a viable technology to bridge this low-frequency technology gap. Recent developments have been propelled by the rapid technology growth in affordable and practical digital signal processing chips and, to a smaller degree, improvements in control transducers. In this article the authors overview the active sound and vibration control field, first by putting it into a historical context, then by outlining the relevant control theory and implementations, and finally by describing some current practical applications.

Fuzzy logic based on-line efficiency optimization control of an indirect vector-controlled induction motor drive

Abstract: Improvement of adjustable speed drive system efficiency is important not only from the viewpoints of energy saving and cooling system operation, but also from the broad perspective of environmental pollution. The paper describes a fuzzy logic based on-line efficiency optimization control of a drive that uses an indirect vector controlled induction motor speed control system in the inner loop. At steady-state light-load condition, a fuzzy controller adaptively decrements the excitation current on the basis of measured input power such that, for a given load torque and speed, the drive settles down to the minimum input power, i.e., operates at maximum efficiency. The low-frequency pulsating torque due to decrementation of rotor flux is compensated in a feedforward manner. If the load torque or speed command changes, the efficiency search algorithm is abandoned and the rated flux is established to get the best transient response. The drive system with the proposed efficiency optimization controller has been simulated with lossy models of the converter and machine, and its performance has been thoroughly investigated. An experimental drive system with the proposed controller implemented on a TMS320C25 digital signal processor, has been tested in the laboratory to validate the theoretical development. >

Artificial Neural Networks for Modelling and Control of Non-Linear Systems

Abstract: Artificial neural networks possess several properties that make them particularly attractive for applications to modelling and control of complex non-linear systems. Among these properties are their universal approximation ability, their parallel network structure and the availability of on- and off-line learning methods for the interconnection weights. However, dynamic models that contain neural network architectures might be highly non-linear and difficult to analyse as a result. Artificial Neural Networks for Modelling and Control of Non-Linear Systems investigates the subject from a system theoretical point of view. However the mathematical theory that is required from the reader is limited to matrix calculus, basic analysis, differential equations and basic linear system theory. No preliminary knowledge of neural networks is explicitly required. The book presents both classical and novel network architectures and learning algorithms for modelling and control. Topics include non-linear system identification, neural optimal control, top-down model based neural control design and stability analysis of neural control systems. A major contribution of this book is to introduce NLq Theory as an extension towards modern control theory, in order to analyze and synthesize non-linear systems that contain linear together with static non-linear operators that satisfy a sector condition: neural state space control systems are an example. Moreover, it turns out that NLq Theory is unifying with respect to many problems arising in neural networks, systems and control. Examples show that complex non-linear systems can be modelled and controlled within NLq theory, including mastering chaos. The didactic flavor of this book makes it suitable for use as a text for a course on Neural Networks. In addition, researchers and designers will find many important new techniques, in particular NLq Theory, that have applications in control theory, system theory, circuit theory and Time Series Analysis.

Symbolic Controller Synthesis for Discrete and Timed Systems

Abstract: This paper presents algorithms for the symbolic synthesis of discrete and real-time controllers. At the semantic level the controller is synthesized by finding a winning strategy for certain games defined by automata or by timed-automata. The algorithms for finding such strategies need, this way or another, to search the state-space of the system which grows exponentially with the number of components. Symbolic methods allow such a search to be conducted without necessarily enumerating the state-space. This is achieved by representing sets of states using formulae (syntactic objects) over state variables. Although in the worst case such methods are as bad as enumerative ones, many huge practical problems can be treated by fine-tuned symbolic methods. In this paper the scope of these methods is extended from analysis to synthesis and from purely discrete systems to real-time systems.

Sliding mode control for gradient tracking and robot navigation using artificial potential fields

Abstract: This paper introduces a sliding mode control strategy for tracking the gradient of an artificial potential field. The control methodology is applicable to fully actuated holonomic robotic systems with n-degrees of freedom. The controller yields exact tracking of the gradient lines and is invariant with respect to parametric uncertainty and disturbances in system dynamics. A detailed case study for mobile robots introduces the equilibrium point placement method for designing harmonic planar potential fields for circular obstacle security zones. Diffeomorph mappings can be utilized for more complex obstacle security zones. The gradient of the harmonic potential field is shown to always lead away from the obstacle security zone and to continuously approach the goal point. >

Active Control of Structures Using Neural Networks

Abstract: A new neural-network-based control algorithm has been developed and tested in the computer simulation of active control of a three-story frame structure subjected to ground excitations. First, an emulator neural network has been trained to forecast the future response of the structure from the immediate history of the system's response, which consists of the structure plus an actuator. The trained emulator has been used in predicting the future responses and in evaluating the sensitivities of the control signal with respect to those responses. At each time step of the simulation, the control signal has been adjusted to induce the required control force in the actuator based in a control criterion. A controller neural network has been trained to learn the relation between the immediate history of response of the structure and actuator, and the adjusted control signals. The trained neurocontroller has been used in controlling the structure for different dynamic loading conditions. Results of this initial st...

A new methodology for designing a fuzzy logic controller

Abstract: A new methodology is proposed for designing a fuzzy logic controller (FLC). A phase plane is used to bridge the gap between the time-response and rule base. The rule base can be easily built using the general dynamics of the process, and then readily updated to contain the delayed information for reducing the deadtime effects of the process. An adaptive gain method is also proposed to help the database design and the controller tuning. Much of the FLC design can be shifted to the design and tuning of gain. A good performance can be achieved both in transient state and steady state without use of multidecision tables. Application of FLC with these new methodologies is presented for a thermal process with a varying deadtime to show the robust performance of FLC and the effectiveness of these methodologies. >

Arbitrary path tracking control of articulated vehicles using nonlinear control theory

Abstract: Designs a path tracking controller for an articulated vehicle (a semitrailer-like vehicle) using time scale transformation and exact linearization. The proposed controller allows articulated vehicles to follow arbitrary paths consisting of arcs and lines, while they are moving forward and/or backward. The experimental result of the 8-shaped path tracking control of the articulated vehicle moving backward is also presented. >