Showing papers on "Control theory published in 2002"

Optimal Control Systems

Abstract: INTRODUCTION Classical and Modern Control Optimization Optimal Control Historical Tour About This Book Chapter Overview Problems CALCULUS OF VARIATIONS AND OPTIMAL CONTROL Basic Concepts Optimum of a Function and a Functional The Basic Variational Problem The Second Variation Extrema of Functions with Conditions Extrema of Functionals with Conditions Variational Approach to Optimal Systems Summary of Variational Approach Problems LINEAR QUADRATIC OPTIMAL CONTROL SYSTEMS I Problem Formulation Finite-Time Linear Quadratic Regulator Analytical Solution to the Matrix Differential Riccati Equation Infinite-Time LQR System I Infinite-Time LQR System II Problems LINEAR QUADRATIC OPTIMAL CONTROL SYSTEMS II Linear Quadratic Tracking System: Finite-Time Case LQT System: Infinite-Time Case Fixed-End-Point Regulator System Frequency-Domain Interpretation Problems DISCRETE-TIME OPTIMAL CONTROL SYSTEMS Variational Calculus for Discrete-Time Systems Discrete-Time Optimal Control Systems Discrete-Time Linear State Regulator Systems Steady-State Regulator System Discrete-Time Linear Quadratic Tracking System Frequency-Domain Interpretation Problems PONTRYAGIN MINIMUM PRINCIPLE Constrained Systems Pontryagin Minimum Principle Dynamic Programming The Hamilton-Jacobi-Bellman Equation LQR System using H-J-B Equation CONSTRAINED OPTIMAL CONTROL SYSTEMS Constrained Optimal Control TOC of a Double Integral System Fuel-Optimal Control Systems Minimum Fuel System: LTI System Energy-Optimal Control Systems Optimal Control Systems with State Constraints Problems APPENDICES Vectors and Matrices State Space Analysis MATLAB Files REFERENCES INDEX

A descriptor system approach to H/sub /spl infin// control of linear time-delay systems

Abstract: The output-feedback H/sub /spl infin// control problem is solved for continuous-time, linear, retarded and neutral-type systems. A delay-dependent solution is obtained in terms of linear matrix inequalities (LMIs) by using a descriptor model transformation of the system and by applying P. Park's inequality (1999) for bounding cross-terms. A state-feedback solution is derived for systems with polytopic parameter uncertainties. An output-feedback controller is then found by solving two LMIs, one of which is associated with a descriptor time-delay "innovation filter". The cases of instantaneous and delayed measurements are considered. Numerical examples are given which illustrate the effectiveness of the new theory.

WMR control via dynamic feedback linearization: design, implementation, and experimental validation

Abstract: The subject of the paper is the motion control problem of wheeled mobile robots (WMRs) in environments without obstacles. With reference to the popular unicycle kinematics, it is shown that dynamic feedback linearization is an efficient design tool leading to a solution simultaneously valid for both trajectory tracking and setpoint regulation problems. The implementation of this approach on the laboratory prototype SuperMARIO, a two-wheel differentially driven mobile robot, is described in detail. To assess the quality of the proposed controller, we compare its performance with that of several existing control techniques in a number of experiments. The obtained results provide useful guidelines for WMR control designers.

Fast terminal sliding-mode control design for nonlinear dynamical systems

Abstract: A fast terminal dynamics is proposed and used in the design of the sliding-mode control for single-input single-output nonlinear dynamical systems. The inherent dynamic properties of the fast terminal sliding modes are explored and conditions to ensure its applicability for control designs are obtained.

Direct adaptive NN control of a class of nonlinear systems

Abstract: In this paper, direct adaptive neural-network (NN) control is presented for a class of affine nonlinear systems in the strict-feedback form with unknown nonlinearities. By utilizing a special property of the affine term, the developed scheme,avoids the controller singularity problem completely. All the signals in the closed loop are guaranteed to be semiglobally uniformly ultimately bounded and the output of the system is proven to converge to a small neighborhood of the desired trajectory. The control performance of the closed-loop system is guaranteed by suitably choosing the design parameters. Simulation results are presented to show the effectiveness of the approach.

Fuzzy logic control for parallel hybrid vehicles

Abstract: In this paper, a fuzzy logic controller is developed for hybrid vehicles with parallel configuration. Using the driver command, the state of charge of the energy storage, and the motor/generator speed, a set of rules have been developed, in a fuzzy controller, to effectively determine the split between the two powerplants: electric motor and internal combustion engine. The underlying theme of the fuzzy rules is to optimize the operational efficiency of all components, considered as one system. Simulation results were used to assess the performance of the controller. A forward-looking hybrid vehicle model was used for implementation and simulation of the controller. Potential fuel economy improvement is shown by using fuzzy logic, relative to other controllers, which maximize only the efficiency of the engine.

Adaptive control of nonlinearly parameterized systems: the smooth feedback case

Abstract: Studies global adaptive control of nonlinearly parameterized systems with uncontrollable linearization. Using a parameter separation technique and the tool of adding a power integrator, we develop a feedback domination design approach for the explicit construction of a smooth adaptive controller that solves the problem of global state regulation. In contrast to the existing results in the literature, a key feature of our adaptive regulator is its minimum-order property, namely, no matter how big the number of unknown parameters is, the order of the dynamic compensator is identical to one, and is therefore minimal. As a consequence, global state regulation of feedback linearizable systems with nonlinear parameterization is achieved by one-dimensional adaptive controllers, without imposing any extra (e.g., convex/concave) conditions on the unknown parameters.

A method of tracking the peak power points for a variable speed wind energy conversion system

Abstract: In this paper, a method of tracking the peak power in a wind energy conversion system (WECS) is proposed, which is independent of the turbine parameters and air density. The algorithm searches for the peak power by varying the speed in the desired direction. The generator is operated in the speed control mode with the speed reference being dynamically modified in accordance with the magnitude and direction of change of active power. The peak power points in the P-/spl omega/ curve correspond to dP/d/spl omega/=0. This fact is made use of in the optimum point search algorithm. The generator considered is a wound rotor induction machine whose stator is connected directly to the grid and the rotor is fed through back-to-back pulse-width-modulation (PWM) converters. Stator flux-oriented vector control is applied to control the active and reactive current loops independently. The turbine characteristics are generated by a DC motor fed from a commercial DC drive. All of the control loops are executed by a single-chip digital signal processor (DSP) controller TMS320F240. Experimental results show that the performance of the control algorithm compares well with the conventional torque control method.

System and method for highly phased power regulation using adaptive compensation control

Abstract: A highly phased power regulation (converter) system having an improved control feature is provided. A controller, such as a digital signal processor or microprocessor, receives digital information from a plurality of power conversion blocks and transmits control commands in response to the information. The controller is able to change the mode of operation of the system and/or re-phase the power blocks to accommodate a dynamic load requirement, occasions of high transient response or detection of a fault. A compensation block within the controller is used to regulate the output voltage and provide stability to the system. In one embodiment, the controller is implemented as a PID compensator controller. In another embodiment, a microprocessor is able to receive feedback on its own operation thus providing enabling the controller to anticipate and predict conditions by analyzing precursor data.

New results on the synthesis of PID controllers

Abstract: This paper considers the problem of stabilizing a first-order plant with dead time using a proportional-integral-derivative (PID) controller. Using a version of the Hermite-Biehler theorem that is applicable to quasi-polynomials, the complete set of stabilizing PID parameters is determined for both open-loop stable and unstable plants. The range of admissible proportional gains is first determined in closed form. For each proportional gain in this range, the stabilizing set in the space of the integral and derivative gains is shown to be either a trapezoid, a triangle or a quadrilateral. For the case of an open-loop unstable plant, a necessary and sufficient condition on the time delay is determined for the existence of stabilizing PID controllers.

An Introduction to Nonlinear Model Predictive Control

Abstract: While linear model predictive control is popular since the 70s of the past century, the 90s have witnessed a steadily increasing attention from control theoretists as well as control practitioners in the area of nonlinear model predictive control (NMPC). The practical interest is driven by the fact that today’s processes need to be operated under tighter performance specifications. At the same time more and more constraints, stemming for example from environmental and safety considerations, need to be satisfied. Often these demands can only be met when process nonlinearities and constraints are explicitly considered in the controller. Nonlinear predictive control, the extension of well established linear predictive control to the nonlinear world, appears to be a well suited approach for this kind of problems. In this note the basic principle of NMPC is reviewed, the key advantages/disadvantages of NMPC are outlined and some of the theoretical, computational, and implementational aspects of NMPC are discussed. Furthermore, some of the currently open questions in the area of NMPC are outlined. 1 Principles, Mathematical Formulation and Properties of Nonlinear Model Predictive Control Model predictive control (MPC), also referred to as moving horizon control or receding horizon control, has become an attractive feedback strategy, especially for linear processes. Linear MPC refers to a family of MPC schemes in which linear models are used to predict the system dynamics, even though the dynamics of the closed-loop system is nonlinear due to the presence of constraints. Linear MPC approaches have found successful applications, especially in the process industries. A good overview of industrial linear MPC techniques can be found in [64, 65], where more than 2200 applications in a very wide range from chemicals to aerospace industries are summarized. By now, linear MPC theory is quite mature. Important issues such as online computation, the interplay between modeling/identification and control and system theoretic issues like stability are well addressed [41, 52, 58]. Many systems are, however, in general inherently nonlinear. This, together with higher product quality specifications and increasing productivity demands, tighter environmental regulations and demanding economical considerations in the process industry require to operate systems closer to the boundary of the admissible operating region. In these cases, linear models are often inadequate to describe the process dynamics and nonlinear models have to be used. This motivates the use of nonlinear model predictive control. This paper focuses on the application of model predictive control techniques to nonlinear systems. It provides a review of the main principles underlying NMPC and outlines the key advantages/disadvantages of NMPC and some of the theoretical, computational, and implementational aspects. Note, however, that it is not intended as a complete review of existing NMPC techniques. Instead we refer to the following list for some excellent reviews [4, 16, 22, 52, 58, 68]. In Section 1.1 and Section 1.2 the basic underlying concept of NMPC is introduced. In Section 2 some of the system theoretical aspects of NMPC are presented. After an outline of NMPC schemes that achieve stability one particular NMPC formulation, namely quasi-infinite horizon NMPC (QIH-NMPC) is outlined to exemplify the basic ideas to achieve stability. This approach allows a (computationally) efficient formulation of NMPC while guaranteeing stability and performance of the closed-loop. Besides the basic question of the stability of the closed-loop, questions such as robust formulations of NMPC and some remarks on the performance of the closed-loop are given in Section 2.3 and Section 2.2. Section 2.4 gives some remarks on the output-feedback problem in connection with NMPC. After a short review of existing approaches one

A review of RFO induction motor parameter estimation techniques

Abstract: An induction motor is the most frequently used electric machine in high-performance drive applications. Control schemes of such drives require an exact knowledge of at least some of the induction motor parameters. Any mismatch between the parameter values used within the controller and actual parameter values in the motor leads to a deterioration in the drive performance. Numerous methods for induction machine on-line and off-line parameter estimation have been developed exclusively for application in high-performance drives. This paper aims at providing a review of the major techniques used for the induction motor parameter estimation. The paper is illustrated throughout with experimental and simulation examples related to various parameter estimation techniques.

Forward models in visuomotor control.

Abstract: In recent years, an increasing number of research projects investigated whether the central nervous system employs internal models in motor control. While inverse models in the control loop can be identified more readily in both motor behavior and the firing of single neurons, providing direct evidence for the existence of forward models is more complicated. In this paper, we will discuss such an identification of forward models in the context of the visuomotor control of an unstable dynamic system, the balancing of a pole on a finger. Pole balancing imposes stringent constraints on the biological controller, as it needs to cope with the large delays of visual information processing while keeping the pole at an unstable equilibrium. We hypothesize various model-based and non-model-based control schemes of how visuomotor control can be accomplished in this task, including Smith Predictors, predictors with Kalman filters, tapped-delay line control, and delay-uncompensated control. Behavioral experiments with human participants allow exclusion of most of the hypothesized control schemes. In the end, our data support the existence of a forward model in the sensory preprocessing loop of control. As an important part of our research, we will provide a discussion of when and how forward models can be identified and also the possible pitfalls in the search for forward models in control.

Switched reluctance generators and their control

Abstract: This paper discusses how the switched reluctance generator (SRG) converts energy as directed by a controller. Beginning with a review of the electromechanics of generation, the paper identifies the implications of the energy conversion process on how the SRG is controlled. The structure of the SRG controller for speed-control and power-control applications is discussed. Practical implementation details for commutation of the SRG are reviewed. Concepts are illustrated with a 6-kW SRG designed to serve as a starter/alternator in automotive applications.

Fuzzy logic controlled shunt active power filter for power quality improvement

Abstract: The simulation and experimental study of a fuzzy logic controlled, three-phase shunt active power filter to improve power quality by compensating harmonics and reactive power required by a nonlinear load is presented. The advantage of fuzzy control is that it is based on a linguistic description and does not require a mathematical model of the system. The fuzzy control scheme is realised on an inexpensive dedicated micro-controller (INTEL 8031) based system. The compensation process is based on sensing line currents only, an approach different from conventional methods, which require harmonics or reactive volt-ampere requirement of the load. The performance of the fuzzy logic controller is compared with a conventional PI controller. The dynamic behavior of the fuzzy controller is found to be better than the conventional PI controller. PWM pattern generation is based on carrierless hysteresis based current control to obtain the switching signals. Various simulation and experimental results are presented under steady state and transient conditions.

Control Theory for Humans: Quantitative Approaches To Modeling Performance

Abstract: Contents: Preface. Perception/Action: A Systems Approach. Closing the Loop. Information Theory and Fitts' Law. The Step Response: First-Order Lag. Linear Systems: Block Diagrams and Laplace Transforms. The Step Response: Second-Order System. Nonproportional Control. Interactions Between Information and Dynamic Constraints. Order of Control. Tracking. There Must Be 50 Ways to See a Sine Wave. A Qualitative Look at Fourier Analysis. The Frequency Domain: Bode Analysis. The Frequency Domain: Describing the Human Operator. Additional Adaptive Aspects of the Crossover Model. Driving Around in Circles. Continuous Tracking: Optimal Control. Estimating and Predicting the State of a Dynamic System With Lag-Like Calculations. Varieties of Variability. Lifting a Glass of Juice. Sine Wave Tracking Is Predictably Attractive. Going With the Flow: An Optical Basis for the Control of Locomotion. Fuzzy Approaches to Vehicular Control. Learning to Control Difficult Systems: Neural Nets. Some Parallels Between Decision Making and Manual Control. Designing Experiments With Control Theory in Mind. Adaptation and Design. Appendix: Interactive Demonstrations.

Adaptive output feedback control of uncertain nonlinear systems using single-hidden-layer neural networks

Abstract: We consider adaptive output feedback control of uncertain nonlinear systems, in which both the dynamics and the dimension of the regulated system may be unknown. However, the relative degree of the regulated output is assumed to be known. Given a smooth reference trajectory, the problem is to design a controller that forces the system measurement to track it with bounded errors. The classical approach requires a state observer. Finding a good observer for an uncertain nonlinear system is not an obvious task. We argue that it is sufficient to build an observer for the output tracking error. Ultimate boundedness of the error signals is shown through Lyapunov's direct method. The theoretical results are illustrated in the design of a controller for a fourth-order nonlinear system of relative degree two and a high-bandwidth attitude command system for a model R-50 helicopter.

Active fault-tolerant control system against partial actuator failures

Abstract: A novel approach for integrated fault detection, diagnosis and reconfigurable control systems design against actuator faults is proposed. The scheme is based on a two-stage adaptive Kalman filter for simultaneous state and fault parameter estimation, statistical decisions for fault detection, and activation of controller reconfiguration. Using the information from the fault detection and diagnosis scheme, the reconfigurable feedback controller is designed automatically based on an eigenstructure assignment technique. To eliminate the steady-state tracking error, a reconfigurable feedforward controller is also incorporated using a command generator tracker technique. The following fault types and input signals are considered: abrupt and incipient, single, multiple and consecutive faults, constant and arbitrarily varying reference inputs. The effectiveness and the superiority of the proposed approach are demonstrated using an aircraft example.

Receding horizon control of autonomous aerial vehicles

Abstract: This paper presents a new approach to trajectory optimization for autonomous fixed-wing aerial vehicles performing large-scale maneuvers. The main result is a planner which designs nearly minimum time planar trajectories to a goal, constrained by no-fly zones and the vehicle's maximum speed and turning rate. Mixed-Integer Linear Programming (MILP) is used for the optimization, and is well suited to trajectory optimization because it can incorporate logical constraints, such as no-fly zone avoidance, and continuous constraints, such as aircraft dynamics. MILP is applied over a receding planning horizon to reduce the computational effort of the planner and to incorporate feedback. In this approach, MILP is used to plan short trajectories that extend towards the goal, but do not necessarily reach it. The cost function accounts for decisions beyond the planning horizon by estimating the time to reach the goal from the plan's end point. This time is estimated by searching a graph representation of the environment. This approach is shown to avoid entrapment behind obstacles, to yield near-optimal performance when comparison with the minimum arrival time found using a fixed horizon controller is possible, and to work consistently on large trajectory optimization problems that are intractable for the fixed horizon controller.

Singular perturbations and time scales in control theory and applications: An overview

Abstract: This paper presents an overview of singular perturbations and time scales (SPaTS) in control theory and applications during the period 1984-2001 (the last such overviews were provided by [231, 371]). Due to the limitations on space, this is in way intended to be an exhaustive survey on the topic.

A comparison of high-power converter topologies for the implementation of FACTS controllers

Abstract: This paper compares four power converter topologies for the implementation of flexible AC transmission system (FACTS) controllers: three multilevel topologies (multipoint clamped (MPC), chain, and nested cell) and the well-established multipulse topology. In keeping with the need to implement very-high-power inverters, switching frequency is restricted to line frequency. The study addresses device count, DC filter ratings, restrictions on voltage control, active power transfer through the DC link, and balancing of DC-link voltages. Emphasis is placed on capacitor sizing because of its impact on the cost and size of the FACTS controller. A method for the dimensioning the DC capacitor filter is presented. It is found that the chain converter is attractive for the implementation of a static compensator or a static synchronous series compensator. The MPC converter is attractive for the implementation of a unified power flow controller or an interline power flow controller, but a special arrangement is required to overcome the limitations on voltage control.

Disturbance Observers for Rigid Mechanical Systems: Equivalence, Stability, and Design

Abstract: Mechanical (direct-drive) systems designed for high-speed and high-accuracy applications require control systems that eliminate the influence of disturbances like cogging forces and friction. One way to achieve additional disturbance rejection is to extend the usual (P(I)D) controller with a disturbance observer. There are two distinct ways to design, represent, and implement a disturbance observer, but in this paper it is shown that the one is a generalization of the other. A general systematic design procedure for disturbance observers that incorporates stability requirements is given. Furthermore, it is shown that a disturbance observer can be transformed into a classical feedback structure, enabling numerous well-known tools to be used for the design and analysis of disturbance observers. Using this feedback interpretation of disturbance observers, it will be shown that a disturbance observer based robot tracking controller can be constructed that is equivalent to a passivity based controller. By this equivalence not only stability proofs of the disturbance observer based controller are obtained, but it also provides more transparent controller parameter selection rules for the passivity based controller.

Wind turbine blade

Abstract: The invention relates to a wind turbine blade with at least one control surface and an actuator inside the main body of the wind turbine blade for moving the control surface, wherein the actuator comprises a fluidic muscle, a controller and a pump, and wherein the fluidic muscle is adapted to change in length and width when the pressure of the fluid within the fluidic muscle is varied.

Speed estimation of an induction motor drive using an optimized extended Kalman filter

Abstract: This paper presents a novel method to achieve good performance of an extended Kalman filter (EKF) for speed estimation of an induction motor drive. A real-coded genetic algorithm (GA) is used to optimize the noise covariance and weight matrices of the EKF, thereby ensuring filter stability and accuracy in speed estimation. Simulation studies on a constant V/Hz controller and a field-oriented controller (FOC) under various operating conditions demonstrate the efficacy of the proposed method. The experimental system consists of a prototype digital-signal-processor-based FOC induction motor drive with hardware facilities for acquiring the speed, voltage, and current signals to a PC. Experiments comprising offline GA training and verification phases are presented to validate the performance of the optimized EKF.