Showing papers presented at "American Control Conference in 1999"

Stability analysis of networked control systems

Abstract: We introduce a control network protocol, try-once-discard (TOD), for networked control systems (NCS), and provide, for the first time, an analytic proof of global exponential stability for both the new protocol and the commonly used statically scheduled access methods Controllers are designed without regarding the presence of the network in the feedback loop, so consequently many controller design techniques may be employed The performance of the new network protocol and the statically scheduled protocols are compared in simulations

Nonlinear model predictive control

Abstract: Nonlinear model predictive control (NMPC) has been introduced in commercial applications. Since mid 1996 approximately 50 applications have been commissioned in polymers, chemicals, food, pulp and paper, and oil refining. This industrial presentation provides a brief overview of the commercial NMPC package and presents a summary of a specific polymers application that was chosen to demonstrate the different nonlinear models that can be used in a NMPC application.

A path-following method for solving BMI problems in control

Abstract: We present a path-following (homotopy) method for (locally) solving bilinear matrix inequality (BMI) problems in control. The method is to linearize the BMI using a first order perturbation approximation, and then iteratively compute a perturbation that "slightly" improves the controller performance by solving a semidefinite program. This process is repeated until the desired performance is achieved, or the performance cannot be improved any further. While this is an approximate method for solving BMIs, we present several examples that illustrate the effectiveness of the approach.

Adaptive robust motion control of single-rod hydraulic actuators: Theory and experiments

Abstract: High performance robust motion control of single-rod hydraulic actuators is considered. In contrast to the double-rod hydraulic actuators studied previously, the two chambers of a single-rod hydraulic actuator have different areas. As a result, the dynamic equations describing the pressure changes in the two chambers cannot be combined into a single load pressure equation. This complicates the controller design since it not only increases the dimension of the system to be dealt with but also brings in the stability issue of the added internal dynamics. A discontinuous projection based adaptive robust controller (ARC) is constructed. The controller is able to take into account not only the effect of parameter variations coming from the inertia load and various hydraulic parameters but also the effect of hard-to-model nonlinearities such as uncompensated friction forces and external disturbances. Extensive experimental results are obtained for the swing motion control of a hydraulic arm. In comparison to a state-of-the-art industrial motion controller, the proposed ARC algorithm achieves more than a magnitude reduction of tracking errors. Furthermore, during constant velocity and regulation periods, the ARC controller reduces the tracking errors almost down to the measurement resolution level.

Design of PID controllers based on constrained optimization

Abstract: This paper presents a new design method for PID controllers based on optimization of load disturbance rejection with constraints on robustness to model uncertainties. The design also delivers parameters to deal with measurement noise and set point response. Thus, the formulation of the design problem captures four essential aspects of industrial control problems, leading to a constrained optimization problem which can be solved iteratively.

Stable multiple model adaptive flight control for accommodation of a large class of control effector failures

Abstract: We propose a new parametrization for the modeling of control effector failures in flight control applications. The failures include float, lock-in-place, hard-over, and loss of effectiveness. It is shown that the resulting representation leads naturally to a multiple model formulation of the corresponding control problem that can be solved using a multiple model adaptive reconfigurable control approach. We derive stable multiple model adaptive reconfigurable control algorithms for the most complex case when one of the effectors undergoes float, lock-in-place or hard-over failure, while all others lose effectiveness. The stability of the overall reconfigurable control system is demonstrated using the Lyapunov method and the separation between identification and control arising in the context of indirect adaptive control. The approach is illustrated through numerical simulations of the F-18 aircraft carrier landing manoeuvre.

Spacecraft formation flying: dynamics and control

Abstract: A concept of a distributed array of small, low-cost, cooperative, and highly coordinated microspacecraft is vigorously being pursued for several future space missions. Implementation of the distributed coordinated spacecraft concept will require tight control of the relative distances and phases between the participating spacecraft. We review nonlinear and linear spacecraft relative position modeling techniques. In addition, we develop a mathematically rigorous control design framework for linear control of spacecraft relative position dynamics with guaranteed closed-loop stability. Finally, illustrative numerical simulations are provided to demonstrate the efficacy of the proposed approach.

Neural networks for control

Abstract: Provides a quick overview of neural networks and explains how they can be used in control systems. We introduce the multilayer perceptron neural network and describe how it can be used for function approximation. The backpropagation algorithm (including its variations) is the principal procedure for training multilayer perceptrons; it is briefly described here. Care must be taken, when training perceptron networks, to ensure that they do not overfit the training data and then fail to generalize well in new situations. Several techniques for improving generalization are discussed. The article also presents several control architectures, such as model reference adaptive control, model predictive control, and internal model control, in which multilayer perceptron neural networks can be used as basic building blocks.

Dynamics and control of micromachined gyroscopes

Abstract: We summarize principles of operation of micromachined gyroscopes, analyze dynamics of ideal and non-ideal systems, and propose an approach for formulation and solving problems of control. The suggested approach uses active nonlinear feedback control for drive and compensation of errors. Both non-adaptive and adaptive strategies are presented. These strategies can be used for a broad class of micromachined vibratory gyroscopes including those for angle and angular rate measurement.

Moving horizon estimation for hybrid systems and fault detection

Abstract: An approach for fault detection and state estimation of hybrid systems is presented. The method relies on the modeling framework for hybrid systems introduced by Bemporad and Morari (1999). This framework considers interacting propositional logic, automata, continuous dynamics and constraints. The proposed approach is illustrated by considering the fault detection problem of the three-tank benchmark system.

Fuzzy descriptor systems: stability analysis and design via LMIs

Abstract: A fuzzy descriptor system is defined Six kinds of stability conditions for the fuzzy descriptor system are derived and represented in terms of linear matrix inequalities (LMIs) The stability analysis is reduced to a problem of finding a common Lyapunov function An LMI design approach is employed to find stable feedback gains and a common Lyapunov function

Tutorial: model predictive control technology

Abstract: This paper provides a brief tutorial on model predictive control (MPC) theory for linear and nonlinear models. The discussion of MPC with linear models covers the topics of steady-state target calculation, infinite horizon receding horizon regulation, resolving infeasibilities caused by constraints, and state estimation and disturbance models. The section on nonlinear models briefly discusses what is desirable from a theoretical perspective and what is possible from an implementation perspective and focuses on some current efforts to bridge this gap. The paper concludes with a brief outlook for future developments in the areas of nonlinear MPC, robustness, moving horizon state estimation and MPC of hybrid systems.

Optimal traffic light control for a single intersection

Abstract: We consider a traffic light controlled intersection. First we construct a model that describes the evolution of the queue lengths (as continuous variables) in each lane. Next, we discuss how optimal and suboptimal traffic light switching schemes (with possibly variable cycle lengths) for this system can be determined. We also show that for a special class of objective functions suboptimal traffic light switching schemes can be computed very efficiently.

A design of self-tuning PID controllers using a genetic algorithm

Abstract: A self-tuning PID controller design scheme is proposed, which is able to deal with systems with unknown or time-varying parameters. The proposed scheme is derived based on the relationship between PID control and generalized minimum variance control (GMVC) laws. Furthermore, a suitable set of some user-specified parameters included in the GMVC criterion is sought by using a genetic algorithm recursively. A numerical simulation example shows the effectiveness of the newly proposed control scheme.

Swing-up control of an inverted pendulum by energy-based methods

Abstract: The mechanical energy of a pendulum whose pivot can move horizontally can be controlled according to signs of the pivot acceleration values. A servo design technique is proposed which can control the pivot acceleration considering a limited travel of the pivot. This control law is applied to the swing-up control problem for an inverted pendulum.

Dual-stage track-following servo design for hard disk drives

Abstract: Discrete time, 25 KTPI track-following servos were designed for magnetic hard disk drive dual stage actuators using the /spl mu/-synthesis methodology. The design methodology was tested on two microactuator models. The first is a model of a piezoelectrically actuated suspension, under development by Hutchinson Technology Incorporated. The second is a model of an electrostatically actuated MEMS microactuator, under development by the IBM Almaden Research Center. Low order controllers were successfully designed for both models, which achieved the prescribed robustness and performance requirements.

On controller design for linear time-invariant dual-input single-output systems

Abstract: Presents a method for the design of controllers for linear time-invariant dual-input/single-output (DISO) systems in continuous-time or discrete-time. The new method reduces the problem to two single input/single-output (SISO) design problems which are well suited to frequency response design techniques. The first part of the method is the design of a stabilizing compensator for an auxiliary feedback system. The auxiliary compensator parameterizes the two output blocks of the single-input/dual-output controller such that the zeros of the parallel system formed by cascade of the controller with the plant are stable. The auxiliary compensator also determines the relative contribution to the output of the two parallel subsystems of the DISO system. The second SISO compensator design is used to ensure that the feedback system is stable and that performance and robustness specifications are achieved. The paper includes a discrete time design example for a dual-stage actuator system for a disk drive. Straightforward extensions for multi input/single-output systems are discussed.

Distillation column identification for control using Wiener model

Abstract: Identification of distillation columns for model based control is studied using Wiener type models. A recently developed parametric identification of Wiener model is extended and used to solve the problem. The method provides solutions to the four problems of identification. It is control relevant and can treat both open-loop and closed-loop data. First the identification method is outlined, then two case studies will be presented, the first one is a simulated high purity distillation column based on first principle models, the second one is a crude unit atmospheric tower.

Necessary and sufficient conditions for the existence of a common quadratic Lyapunov function for two stable second order linear time-invariant systems

Abstract: In this paper, necessary and sufficient conditions are derived for the existence of a common quadratic Lyapunov function for M (>2) stable second order linear time-invariant systems.

Stabilizing receding horizon control of nonlinear systems: a control Lyapunov function approach

Abstract: A modified version of the receding horizon control of nonlinear systems is proposed. The approach is based on a finite horizon optimal control problem with a terminal cost. This method can be treated as an extension of results of De Nicolao et al. (1998). To the case where a control Lyapunov function (CLF)-based stabilizing control law is available. The terminal cost is picked to be a CLF which is also an upper bound on the cost-to-go if the stabilizing control law is applied. The control law is computed a priori using a CLF. Effectiveness of the results is illustrated by applying this approach to the planar model of a ducted fan with a CLF obtained using quasi LPV methods.

Adaptive nonlinear friction compensation with parametric uncertainties

Abstract: Two adaptive nonlinear friction compensation schemes are proposed to handle two types of parametric uncertainty in the LuGre dynamic friction model: non-uniform friction force variations and normal force variations. Our design features a dual-observer structure to estimate different nonlinear effects of the unmeasurable friction state. Using the estimated friction parameters and the dual observers for the unmeasurable friction state, adaptive nonlinear controllers are designed to achieve globally asymptotic tracking of the given velocity reference signal.

A model predictive control-based approach for spacecraft formation keeping and attitude control

Abstract: In this paper we report on the application of a model predictive control-based approach to the design of a controller for formation keeping and formation attitude control, with applications to spacecraft formation flight problems such as NASA's DS3 mission. Control laws for formation keeping and attitude control are designed using a combined approach of feedback linearization and model predictive control. Actuator saturation is incorporated into the controller design. Switching between coordinated frames is incorporated to overcome singularities associated with local feedback linearization.

Piezoelectric scanners for atomic force microscopes: design of lateral sensors, identification and control

Abstract: This paper presents the identification and control of piezoelectric positioners used in atomic force microscopes (AFM) with the goal of improving probe positioning on the sample surface. A novel sensor was developed for this task and employed to infer a sixth order linear two input two output model of the piezo's lateral dynamics. The piezo model was used to design a controller for tracking reference signals common in AFM operation. The controller and sensor were shown to significantly improve the microscope's ability to position the probe on the sample's surface, enabling the AFM user to precisely scan areas on a surface based on images from previous scans.

Model-free subspace-based LQG-design

Abstract: When only input/output data of an unknown system are available, the classical way to design a linear quadratic Gaussian controller for that system mainly consists of three separate parts. First a system identification step is performed to find the system parameters. With these parameters a Kalman filter is designed to find an estimate of the state of the system. Finally, this state is then used in an LQ-controller. In the literature these three steps are hardly ever considered as one joint problem. Based on techniques from the field of sub-space system identification the present paper gives a new, much more direct method to calculate a finite-horizon LQG-controller. The three steps of the LQG-controller design, i.e. system identification, Kalman filter and LQ-control design are replaced by a QR- and a SV-decomposition. The equivalence between the new subspace-based approach and the classical approach is proven.

Lateral and longitudinal vehicle control coupling for automated vehicle operation

Abstract: This paper covers developments in the control integration part of the automated highway system (AHS) program of the California Partners for Advanced Transportation and Highways (PATH). The control integration project investigates the potential for improving controller performance through an integrated design of a combined steering and speed controller specifically designed to address the coupling between the steering and speed controls. The following results are presented: (1) the identification and characterization of the various coupling effects through an analysis of vehicle dynamics; (2) the design of a combined controller which compensates for the coupling effects; and, (3) the evaluation of the improvements contributed by the coupling compensation through simulations and through experiments on full-scale test vehicles. Sliding control and dynamic surface control (DSC) methods are used to facilitate the inclusion of the complex, nonlinear coupling effects in the controller derivation. A multiple-rate observer is designed to obtain a lateral velocity estimate which is essential to the implementation of the controller on the test vehicle. Simulations and experiments show that the coupling compensation does improve controller performance and that the combined controller is robust to modeling imperfections and vehicle parameter variations. The combined controller described in this paper may be the ideal basis for future implementation of the automated highway system.

Adaptive control of systems with backlash hysteresis at the input

Abstract: A new compact dynamical model for backlash inverse is presented. This model may be utilized for both backlash at the input or at the output. Two cases are considered: the case where the backlash spacing is known as well as the case of unknown backlash spacing. For the latter case, an adaptive update law is developed to compensate for the unknown spacing. The adaptive backlash inverse controller is a break-away from existing backlash compensators which are mostly implemented in discrete-time and utilize complex control algorithms. The advocated results are applied to a one degree-of-freedom system affected by backlash. The stability of the closed-loop system is shown using Lyapunov arguments. Simulation results show that the control methodology greatly improves tracking performance over a PD type controller.

Controller performance assessment based on setpoint response data

Abstract: A new methodology is developed to assess the performance of PI controllers from closed-loop response data for a setpoint step change. It is based on two new dimensionless performance indices, the dimensionless settling time and the dimensionless integral of the absolute value of the error. The methodology is used to quantify how far a control loop is from the best achievable performance of PI control. It also identifies poorly performing control loops, such as those that are excessively sluggish. The performance and robustness properties of the internal model control (IMC) tuning method are analyzed and are used as industrially relevant benchmarks. The proposed methodology is also applicable to PID controllers.

Experimental verification of a command shaping boom crane control system

Abstract: Presents experimental results of a command shaping control method for suppressing payload swing caused by operator commanded manoeuvres, in rotary, ship-based, boom cranes The crane configuration investigated, consists of a payload mass that swings on the end of a spherical pendulum of varying lift-line length (hoisting) The lift-line is attached to a boom capable of elevation (luffing) and rotation about a vertical axis (slewing) Positioning of the payload is accomplished through luff, slew and hoist commands issued in real-time by an operator The command shaping strategy, consisting of a time-varying filter, reduces payload oscillation by 18 dB in experiments using the 1/16th scale Navy Crane Testbed at Sandia National Laboratories

Control of LQG systems under communication constraints

Abstract: We consider the control performance of an LQG system with a noisy analog feedback channel between the state-observation and the controller. To bound the performance, we use the sequential rate distortion function and the assumption of equi-memory. We then discuss the trade-offs between control and communication costs and how to relax the equi-memory assumption.

Adaptive neural network control for strict-feedback nonlinear systems using backstepping design

Abstract: This paper focuses on the adaptive control problem of strict-feedback nonlinear systems using multilayer neural networks (MNNs). By introducing a modified Lyapunov function, a smooth and singularity-free adaptive controller is first designed for a first-order plant. Then, an extension is made to high-order nonlinear systems using backstepping design. The control scheme developed guarantees the uniform ultimate boundedness of the closed-loop adaptive systems. The relationship between the transient performance and the design parameters is given to guide the tuning of the controller.