Showing papers on "Control theory published in 1994"
TL;DR: In this paper, the continuous and discrete-time H∞ control problems are solved via elementary manipulations on linear matrix inequalities (LMI), and two interesting new features emerge through this approach: solvability conditions valid for both regular and singular problems, and an LMI-based parametrization of all H ∞-suboptimal controllers, including reduced-order controllers.
Abstract: The continuous- and discrete-time H∞ control problems are solved via elementary manipulations on linear matrix inequalities (LMI). Two interesting new features emerge through this approach: solvability conditions valid for both regular and singular problems, and an LMI-based parametrization of all H∞-suboptimal controllers, including reduced-order controllers.
The solvability conditions involve Riccati inequalities rather than the usual indefinite Riccati equations. Alternatively, these conditions can be expressed as a system of three LMIs. Efficient convex optimization techniques are available to solve this system. Moreover, its solutions parametrize the set of H∞ controllers and bear important connections with the controller order and the closed-loop Lyapunov functions.
Thanks to such connections, the LMI-based characterization of H∞ controllers opens new perspectives for the refinement of H∞ design. Applications to cancellation-free design and controller order reduction are discussed and illustrated by examples.
3,200 citations
TL;DR: It is shown how this framework can handle standard issues such as the analysis of stability and performance with or without uncertainties in the plant model, and robustness issues are problems in their own right and hence not detailed here.
986 citations
TL;DR: A fuzzy controller is designed which guarantees stability of the control system under a condition and the simulation results show that the designed fuzzy controller smoothly achieves backing up control of the truck-trailer from all initial positions.
Abstract: A robust stabilization problem for fuzzy systems is discussed in accordance with the definition of stability in the sense of Lyapunov. We consider two design problems: nonrobust controller design and robust controller design. The former is a design problem for fuzzy systems with no premise parameter uncertainty. The latter is a design problem for fuzzy systems with premise parameter uncertainty. To realize two design problems, we derive four stability conditions from a basic stability condition proposed by Tanaka and Sugeno: nonrobust condition, weak nonrobust condition, robust condition, and weak robust condition. We introduce concept of robust stability for fuzzy control systems with premise parameter uncertainty from the weak robust condition. To introduce robust stability, admissible region and variation region, which correspond to stability margin in the ordinary control theory, are defined. Furthermore, we develop a control system for backing up a computer simulated truck-trailer which is nonlinear and unstable. By approximating the truck-trailer by a fuzzy system with premise parameter uncertainty and by using concept of robust stability, we design a fuzzy controller which guarantees stability of the control system under a condition. The simulation results show that the designed fuzzy controller smoothly achieves backing up control of the truck-trailer from all initial positions. >
773 citations
TL;DR: These simulations suggest that recurrent controller networks trained by Kalman filter methods can combine the traditional features of state-space controllers and observers in a homogeneous architecture for nonlinear dynamical systems, while simultaneously exhibiting less sensitivity than do purely feedforward controller networks to changes in plant parameters and measurement noise.
Abstract: Although the potential of the powerful mapping and representational capabilities of recurrent network architectures is generally recognized by the neural network research community, recurrent neural networks have not been widely used for the control of nonlinear dynamical systems, possibly due to the relative ineffectiveness of simple gradient descent training algorithms. Developments in the use of parameter-based extended Kalman filter algorithms for training recurrent networks may provide a mechanism by which these architectures will prove to be of practical value. This paper presents a decoupled extended Kalman filter (DEKF) algorithm for training of recurrent networks with special emphasis on application to control problems. We demonstrate in simulation the application of the DEKF algorithm to a series of example control problems ranging from the well-known cart-pole and bioreactor benchmark problems to an automotive subsystem, engine idle speed control. These simulations suggest that recurrent controller networks trained by Kalman filter methods can combine the traditional features of state-space controllers and observers in a homogeneous architecture for nonlinear dynamical systems, while simultaneously exhibiting less sensitivity than do purely feedforward controller networks to changes in plant parameters and measurement noise. >
586 citations
TL;DR: In this paper, a new Smith predictor for control of a process with an integrator and long dead-time is proposed, which decouples the setpoint response from the load response.
Abstract: A new Smith predictor for control of a process with an integrator and long dead-time is proposed in this note. The controller decouples the setpoint response from the load response. This simplifies both design and tuning. Simulation results obtained by controlling a typical process show that the new controller has superior performance compared to previous algorithms. >
521 citations
29 Jun 1994
TL;DR: In this article, the authors give a historical view of linear matrix inequalities in control and system theory, and it appears that linear matrices have been involved in some of the major events of control theory.
Abstract: The purpose of this paper is to give a historical view of linear matrix inequalities in control and system theory. Not surprisingly, it appears that LMIs have been,involved in some of the major events of control theory. With the advent of powerful convex optimization techniques, LMIs are now about to become an important practical tool for future control applications.
484 citations
TL;DR: In this paper, an extended Kalman filter is employed to identify the speed of an induction motor and rotor flux based on the measured quantities such as stator currents and DC link voltage.
Abstract: A vector control of an induction motor by an estimated speed using an extended Kalman filter is proposed. With this method, the states are composed of stator current and rotor flux. The rotor speed is regarded as a parameter, and the composite states consist of the original states and the rotor speed. The extended Kalman filter is employed to identify the speed of an induction motor and rotor flux based on the measured quantities such as stator currents and DC link voltage. The estimated speed is used for vector control and overall speed control. Since the current control is performed at a synchronous rotating reference frame, the estimated speed information is also used for the reference frame transformation of the current controller. Computer simulations and experiments of the speed control have been carried out to test the usefulness of the speed estimation algorithm. The experimental results show that the performance of the speed estimation is very good. >
456 citations
14 Dec 1994
TL;DR: This paper describes a method for constructing a petri net feedback controller for a discrete event system modeled by a Petri net that enforces a set of linear constraints on the plant and consists of places and arcs.
Abstract: This paper describes a method for constructing a Petri net feedback controller for a discrete event system modeled by a Petri net. The controller enforces a set of linear constraints on the plant and consists of places and arcs. It is computed using the concept of Petri net place invariants. The size of the controller is proportional to the number of constraints which must be satisfied. The method is very attractive computationally, and it makes possible the systematic design of Petri net controllers for complex industrial systems. >
TL;DR: Model reference adaptive controllers are designed for plants with unknown dead-zones in which two sets of adjustable parameters, one belonging to a dead-zone inverse and the other to a linear controller, are kept fixed or adaptively updated.
Abstract: Model reference adaptive controllers are designed for plants with unknown dead-zones. Several control strategies are investigated in which two sets of adjustable parameters, one belonging to a dead-zone inverse and the other to a linear controller, are either kept fixed or adaptively updated. The developed adaptive control schemes ensure boundedness of all closed-loop signals and reduce the tracking error. >
08 May 1994
TL;DR: The design of a machine which is composed of homogeneous mechanical units, and the control software of the unit which realizes "self-assembly," one of the basic functions of this machine is developed.
Abstract: The design of a machine which is composed of homogeneous mechanical units is described. We show the design of both hardware and control software of the unit. Each unit can connect with other units and change the connection by itself. In spite of its simple mechanism, a set of these units realizes various mechanical functions. We developed the control software of the unit which realizes "self-assembly," one of the basic functions of this machine. A set of these units can form a given shape of the whole system by themselves. The units exchange information about local geometric relation by communication, and cooperate to form the whole shape through a diffusion-like process. There is no upper level controller to supervise these units, and the software of each unit is completely the same. Three actual units have been built to test the basic movements, and the function of self-assembly has been verified by computer simulation. >
01 Jun 1994
TL;DR: The stability and convergence results for dynamic programming-based reinforcement learning applied to linear quadratic regulation (LQR) are presented and the specific algorithm is based on Q-learning and it is proven to converge to an optimal controller.
Abstract: In this paper we present the stability and convergence results for dynamic programming-based reinforcement learning applied to linear quadratic regulation (LQR). The specific algorithm we analyze is based on Q-learning and it is proven to converge to an optimal controller provided that the underlying system is controllable and a particular signal vector is persistently excited. This is the first convergence result for DP-based reinforcement learning algorithms for a continuous problem.
Patent•
06 Jan 1994TL;DR: In this paper, an interactive robotic therapist interacts with a patient to shape the motor skills of the patient by guiding the patient's limb through a series of desired exercises with a robotic arm.
Abstract: An interactive robotic therapist interacts with a patient to shape the motor skills of the patient by guiding the patient's limb through a series of desired exercises with a robotic arm. The patient's limb is brought through a full range of motion to rehabilitate multiple muscle groups. A drive system coupled to the robotic arm is controlled by a controller which provides the commands to direct the robotic arm through the series of desired exercises.
01 Jan 1994
TL;DR: A new Smith predictor for control of a process with an integrator and long dead-time is proposed in this note, where the controller deeouples the setpoint response from the load response.
Abstract: Abstmct-A new Smith predictor for control of a process with an integrator and long dead-time is proposed in this note. The controller deeouples the setpoint response from the load response. This simplifies both design and tuning. Simulation results obtained by controlling a typical process show that the new controller has superior performance compared to previous algorithms.
TL;DR: It is shown that the communication specific phenomena inducing random communication delays (such as multirate sampling, vacant sampling and message rejection) may be encompassed by finite-dimensional linear discrete-time models, provided that the plant and the controller are linear and time invariant.
Abstract: Integral control of large-scale systems implies coordination of activities by information exchange via communication networks. Usually these networks are shared with other users. Thus traffic conditions in the network may introduce time-varying random delays in the control loop with adverse effects on its performance and stability. Hence, the control must be designed to compensate for these delays. Recent work in modelling integrated control and communication systems has shown that the communication specific phenomena inducing random communication delays (such as multirate sampling, vacant sampling and message rejection) may be encompassed by finite-dimensional linear discrete-time models, provided that the plant and the controller are linear and time invariant. Existing approaches to the design of integrated control systems rely on conservative stability tests, because only sufficient stability conditions were found for systems with random time-varying delays. In this paper, necessary and sufficient cond...
TL;DR: A single-input-single-output nonlinear system which has a uniform relative degree equal to the dimension of the state vector and a robust state feedback control designed to drive the error to a positively invariant set that contains the origin is considered.
TL;DR: An adaptive control scheme for the attitude control of a rigid spacecraft is derived using a linear parameterization of the equation of motion that allows for the use of time-varying positive-definite feedback gain matrices.
Abstract: An adaptive control scheme for the attitude control of a rigid spacecraft is derived using a linear parameterization of the equation of motion. The tracking error is described with the Euler parameter vector. Global convergence of the tracking error to zero is shown using passivity theory. This allows for the use of time-varying positive-definite feedback gain matrices, and the results can easily be extended to other passive parameter update laws. >
TL;DR: In this paper, the problem of synthesizing an internally stabilizing linear time-invariant controller for a linear time invariant plant such that a given closed-loop transfer function is extended strictly positive real was studied.
Abstract: In this paper we study the problem of synthesizing an internally stabilizing linear time-invariant controller for a linear time-invariant plant such that a given closed-loop transfer function is extended strictly positive real. Necessary and sufficient conditions for the existence of a controller are obtained. State-space formulas for the controller design are given in terms of solutions to algebraic Riccati equations (or inequalities). The order of the constructed controller does not exceed that of the plant. >
TL;DR: The design principle, tracking performance, and stability analysis of a fuzzy proportional-derivative (PD) controller, derived from the conventional continuous-time linear PD controller, and the fuzzification, control-rule base, and defuzzification in the design are discussed in detail.
Abstract: This paper describes the design principle, tracking performance, and stability analysis of a fuzzy proportional-derivative (PD) controller. First, the fuzzy PD controller is derived from the conventional continuous-time linear PD controller. Then, the fuzzification, control-rule base, and defuzzification in the design of the fuzzy PD controller are discussed in detail. The resulting controller is a discrete-time fuzzy version of the conventional PD controller, which has the same linear structure in the proportional and the derivative parts but has nonconstant gains: both the proportional and derivative gains are nonlinear functions of the input signals. The new fuzzy PD controller thus preserves the simple linear structure of the conventional PD controller yet enhances its self-tuning control capability. Computer simulation results have demonstrated this advantage of the fuzzy PD controller, particularly when the process to be controlled is nonlinear. After a detailed stability analysis, where a simple and realistic sufficient condition for the bounded-input/bounded-output stability of the overall feedback control system was derived, several computer simulation results are compared with the conventional PD controller. Although the conventional and fuzzy PD controllers are not exactly comparable, the authors compare them in order to have a sense of how well the fuzzy PD controller performs. For this reason, in the simulations several first-order and second-order linear systems, with or without time-delays, are first used to test the performance of the fuzzy PD controller for step reference inputs: the fuzzy PD control systems show remarkable performance, as well as (if not better than) the conventional PD control systems. Moreover, the fuzzy PD controller is compared to the conventional PD controller for a particular second-order linear system, showing the advantage of the fuzzy PD controller over the conventional one in the sense that in order to obtain the same control performance the conventional PD controller has to employ an extremely large gain while the fuzzy controller uses a reasonably small gain. Finally, in the case of nonlinear systems, the authors provide some examples to show that the fuzzy PD controller can track the set-points satisfactorily but the conventional PD controller cannot. >
TL;DR: In this paper, the authors present the development of robust digital tracking control algorithms and their real-time implementation on an electrohydraulic servo-actuator for tool positioning in norcircular machining.
Abstract: This paper presents the development of robust digital tracking control algorithms and their real-time implementation on an electrohydraulic servo-actuator for tool positioning in norcircular machining. Robust adaptive feedforward controller for tracking arbitrary signals and robust repetitive controller for tracking periodic signals against disturbances and unmodeled dynamics have been developed. Experimental results are presented to illustrate the control system synthesis procedures and tracking performance
29 Jun 1994
TL;DR: The bilinear matrix inequality (BMI) as mentioned in this paper is an extension of the linear matrix inequality approach that has recently been found to be useful in formulating and solving a limited class of robust control problems, including statefeedback and full-order dynamical output feedback.
Abstract: This paper introduces the bilinear matrix inequality (BMI) as a simple but flexible framework for approaching robust control system synthesis problems. The BMI is an extension of the linear matrix inequality (LMI) approach that has recently been found to be useful in formulating and solving a limited class of robust control problems, including state-feedback and full-order dynamical output feedback /spl Hscr//sup /spl infin// control, /spl mu//k/sub m/ analysis, simultaneous stabilization, gain-scheduling, and so forth. In particular, the BMI formulation is shown to offer the advantage of handling specifications not amenable to the LMI framework such as constraints on controller structure (e.g., decentralized "block-diagonal" control) and on controller order. The BMI formulation also sheds new insight into the properties and limitations of existing robust control algorithms such as the /spl mu//k/sub m/-synthesis, raising questions about the local optimality of the classical DK-iteration.
Patent•
15 Jun 1994
TL;DR: In this paper, an apparatus and method of tracking and reporting the location of a mobile article, such as a stolen motor vehicle, is presented. But the method is limited to the case of a single mobile article.
Abstract: An apparatus and method of tracking and reporting the location of a mobile article, such as a stolen motor vehicle. A controller receives and analyzes positioning signals transmitted from known locations to determine the location of the motor vehicle. The controller contacts a central tracking station to report the theft and the location of the motor vehicle.
20 Jun 1994
TL;DR: In this article, a new maximum power point tracker (MPPT) using fuzzy set theory is proposed to improve the energy conversion efficiency of photovoltaic systems, where a fuzzy algorithm based on linguistic rules describing the operator's control strategy is applied to control the step-up converter for the MPPT.
Abstract: Studies on photovoltaic systems are increasing because of a large, secure, essentially exhaustible and broadly available resource as a future energy supply. However, the output power induced in the photovoltaic modules is influenced by an intensity of solar cell radiation, temperature of the solar cells and so on. Therefore, to maximize the efficiency of the renewable energy system, it is necessary to track the maximum power point of the input source. In this paper, a new maximum power point tracker (MPPT) using fuzzy set theory is proposed to improve energy conversion efficiency. A fuzzy algorithm based on linguistic rules describing the operator's control strategy is applied to control the step-up converter for the MPPT. Fuzzy logic control based on coarse and fine mode has been incorporated in order to reduce not only the time required to track the maximum power point but also the fluctuation of power. The MPPT algorithm is implemented by a 16 bit single chip 80C196KB microcontroller. Simulation and experimental results show that performance of the fuzzy controller in a maximum power tracking of a photovoltaic array is better than that of controller based upon the hill climbing method. >
TL;DR: In recent years, a wide range of nonlinear methods for feedback control, state estimation, and parameter identification have emerged, and some of these results are reviewed and summarized.
Abstract: Due to the increasing availability of improved power electronics and digital processors at reduced costs, there has been a trend to seek higher performance from electric machine systems through the design of more sophisticated control systems software. There exist significant challenges in the search for improved control system designs, however, since: the dynamics of most electric machine systems exhibit significant nonlinearities; not all state variables are necessarily measured; and the parameters of the system can vary significantly from their nominal values. In recent years, a wide range of nonlinear methods for feedback control, state estimation, and parameter identification have emerged, and some of these results are reviewed and summarized. >
TL;DR: This paper shows that associated control synthesis problems of Ramadge-Wonham type can be efficiently solved under mild technical restrictions, using elementary methods combined with linear integer programming.
Abstract: This paper shows that associated control synthesis problems of Ramadge-Wonham type can be efficiently solved under mild technical restrictions, using elementary methods combined with linear integer programming. Both memoryless and dynamic state feedback are treated. Structural conditions are provided under which the controller can be computed in "closed-form," namely represented as a VDES or "generalized" VDES (GVDES). The results are applied to a model of an AGV system, adapted from work of Holloway and Krogh (1990). >
TL;DR: A new approach to adaptive control oflinear systems abandons the traditional certainty-equivalence concept and treats the control of linear plants with unknown parameters as a nonlinear problem, which significantly improves transient performance without an increase in control effort.
Abstract: A new approach to adaptive control of linear systems abandons the traditional certainty-equivalence concept and treats the control of linear plants with unknown parameters as a nonlinear problem. A recursive design procedure introduces at each step new design parameters and incorporates them in a novel Lyapunov function. This function encompasses all the states of the adaptive system and forces them to converge to a manifold of smallest possible dimension. Only as many controller parameters are updated as there are unknown plant parameters, and the dynamic order of the resulting controllers is no higher (and in most cases is lower) than that of traditional adaptive schemes. A simulation comparison with a standard indirect linear scheme shows that the new nonlinear scheme significantly improves transient performance without an increase in control effort. >
Patent•
10 Nov 1994
TL;DR: In this paper, a theatrical lighting control network is described, which incorporates a local area network for communication among a number of node controllers and control consoles or devices employed in establishing lighting or other effects levels in a theater, film production stage or other performance environment.
Abstract: A theatrical lighting control network is disclosed which incorporates a local area network for communication among a number of node controllers and control consoles or devices employed in establishing lighting or other effects levels in a theater, film production stage or other performance environment. Use of the network eliminates the requirements for the majority of hardwiring for interconnection of consoles and other controller or monitoring devices to effects controller racks and provides great flexibility in location and relocation of various components of the system.
14 Dec 1994
TL;DR: In this article, a semiglobal adaptive output feedback controller is proposed to ensure that the output of the system tracks any given reference signal which is bounded and has bounded derivatives up to the (n+l)th order.
Abstract: We consider a single-input-single-output nonlinear system which can be represented globally by an explicit input-output model. The system is input-output linearizable by feedback and is required to satisfy a minimum phase condition. The nonlinearities are not required to satisfy any global growth condition. The model depends linearly on unknown parameters which belong to a known compact, convex set. We design a semiglobal adaptive output feedback controller which ensures that the output of the system tracks any given reference signal which is bounded and has bounded derivatives up to the (n+l)th order, where n is the order of the system. The reference signal and its derivatives are assumed to belong to a known compact set. It is also assumed to be sufficiently rich to satisfy a persistence of excitation condition. The design process is simple. First we assume that the output and its derivatives are available for feedback and design the adaptive controller as a state feedback controller in appropriate coordinates. Then we saturate the controller outside a domain of interest and use a high-gain observer to estimate the derivatives of the output. We prove, via asymptotic analysis, that when the speed of the high-gain observer is sufficiently high, the adaptive output feedback controller recovers the performance achieved under the state feedback one. >