Showing papers on "Control theory published in 1987"

Supervisory control of a class of discrete event processes

Abstract: This paper studies the control of a class of discrete event processes, i.e. processes that are discrete, asynchronous and possibly nondeter-ministic. The controlled process is described as the generator of a formal language, while the controller, or supervisor, is constructed from the grammar of a specified target language that incorporates the desired closed-loop system behavior. The existence problem for a supervisor is reduced to finding the largest controllable language contained in a given legal language. Two examples are provided.

Discrete-time control systems

Abstract: Discrete-time control systems , Discrete-time control systems , مرکز فناوری اطلاعات و اطلاع رسانی کشاورزی

A hierarchical neural-network model for control and learning of voluntary movement

Abstract: In order to control voluntary movements, the central nervous system (CNS) must solve the following three computational problems at different levels: the determination of a desired trajectory in the visual coordinates, the transformation of its coordinates to the body coordinates and the generation of motor command. Based on physiological knowledge and previous models, we propose a hierarchical neural network model which accounts for the generation of motor command. In our model the association cortex provides the motor cortex with the desired trajectory in the body coordinates, where the motor command is then calculated by means of long-loop sensory feedback. Within the spinocerebellum — magnocellular red nucleus system, an internal neural model of the dynamics of the musculoskeletal system is acquired with practice, because of the heterosynaptic plasticity, while monitoring the motor command and the results of movement. Internal feedback control with this dynamical model updates the motor command by predicting a possible error of movement. Within the cerebrocerebellum — parvocellular red nucleus system, an internal neural model of the inverse-dynamics of the musculo-skeletal system is acquired while monitoring the desired trajectory and the motor command. The inverse-dynamics model substitutes for other brain regions in the complex computation of the motor command. The dynamics and the inverse-dynamics models are realized by a parallel distributed neural network, which comprises many sub-systems computing various nonlinear transformations of input signals and a neuron with heterosynaptic plasticity (that is, changes of synaptic weights are assumed proportional to a product of two kinds of synaptic inputs). Control and learning performance of the model was investigated by computer simulation, in which a robotic manipulator was used as a controlled system, with the following results: (1) Both the dynamics and the inverse-dynamics models were acquired during control of movements. (2) As motor learning proceeded, the inverse-dynamics model gradually took the place of external feedback as the main controller. Concomitantly, overall control performance became much better. (3) Once the neural network model learned to control some movement, it could control quite different and faster movements. (4) The neural netowrk model worked well even when only very limited information about the fundamental dynamical structure of the controlled system was available. Consequently, the model not only accounts for the learning and control capability of the CNS, but also provides a promising parallel-distributed control scheme for a large-scale complex object whose dynamics are only partially known.

Optimal control theory with economic applications

Abstract: Calculus of Variations. Optimal Control Theory Without Restrictions On The State Variables. Extensions. Mixed Constraints. Pure State Constraints. Mixed and Pure State Constraints.

Active noise control systems

Abstract: A retrospective review of the development of active noise control systems is presented, arguing that the design of active noise control (ANC) systems should be considered from a control systems point of view. This approach provides a design methodology that accounts for the design parameters of the system which determine its performance, thereby producing an ANC system that reduces the problems associated with, and the limited practical success of, previous techniques. Based on this argument, the fundamental conditions required for cancellation are derived in terms of the power spectral densities of the primary and secondary waves. These conditions are in turn related to the geometry-related (incorporating the acoustic response of the propagation medium) and source-related parameters of the system. From these conditions, the control structures employed in current ANC systems are examined and compared with the reported applications. A method for the design of controllers for use in ANC systems with broadband compact noise sources suitable for implementation on digital signal processing devices is presented. Using this method, experimental results using differing controllers are illustrated and discussed for both synthetic and practical sources. Finally, current developments in ANC systems are summarised and areas for further work are suggested.

Microprocessor-Controlled DC Motor for Load-Insensitive Position Servo System

Abstract: The conventional proportional P controller has been often used as the position controller of the dc servo motor. When the unknown and inaccessible load torque, such as the coulomb friction, the gravity, and so on, is imposed on the dc servo motor, this control system has the steady-and/or transient-state error.

Stable execution of contact tasks using impedance control

Abstract: This paper presents an experimental evaluation of the performance of a nonlinear robot control algorithm on a contact task involving free motion, constrained motion and transitions between the two. The algorithm is an implementation of impedance control which uses end-point force feedback. Stable control of the force exerted on a rigid surface is achieved without recourse to a soft sensor. Motion control is achieved without inverse kinematic computations. It is unnecessary to switch between different modes of control at the moment of contact as the impedance controller is competent in all phases of the task.

Control of linear systems using generalized sampled-data hold functions

Abstract: This paper investigates the use of generalized sampled-data hold functions (GSHF) in the control of linear time-invariant systems. The idea of GSHF is to periodically sample the output of the system, and generate the control by means of a hold function applied to the resulting sequence. The hold function is chosen based on the dynamics of the system to be controlled. This method appears to have several advantages over dynamic controllers: it has the efficacy of state feedback without the requirement of state estimation; it provides the control system designer with substantially more freedom; and it requires few on-line computations. This paper focuses on four questions: pole assignment, specific behavior, noise sensitivity, and robustness. Among the problems solved are: simultaneous arbitrary pole assignment for a finite number of systems by a single GSHF controller, exact model matching, decoupling, and optimal noise rejection. Examples are given.

Adaptive manipulator control a case study

Abstract: Earlier work (Slotine and Li, 1986) exploits the particular structure of manipulator dynamics to develop a simple, globally convergent adaptive algorithm for trajectory control problems. The algorithm does not require measurements or estimates of the manipulator's joint accelerations, nor inversion of the estimated inertia matrix. This paper demonstrates the approach on a high-speed 2 d.o.f. semi-direct-drive robot. It shows that the manipulator mass properties, assumed to be initially unknown, can be precisely estimated within the first half second of a typical run. Similarly, the algorithm allows large loads of unknown mass properties to be precisely manipulated. Further, these experimental results demonstrate that the adaptive controller enjoys essentially the same level of robustness to unmodelled dynamics as a PD controller, yet achieves much better tracking accuracy than either PD or computed-torque schemes. Its superior performance for high speed operations, in the presence of parameter uncertainties, and its relative computational simplicity, make it a attractive option both to address complex industrial tasks, and to simplify high-level programming of more standard operations.

Linear control theory with an H ∞ 0E optimality criterion

Abstract: This expository paper sets out the principal results in ${\bf H}_\infty $ control theory in the context of continuous-time linear systems. The focus is on the mathematical theory rather than computational methods.

Sensor-based control of robotic manipulators using a general learning algorithm

Abstract: A practical learning control system is described which is applicable to the control of complex robotic systems involving multiple feedback sensors and multiple command variables during both repetitive and nonrepetitive operations. In the controller, a general learning algorithm is used to learn to reproduce the relationship between the sensor outputs and the system command variables over particular regions of the system state space. The learned information is then used to predict the command signals required to produce desired changes in the sensor outputs. The learning controller requires no a priori knowledge of the relationships between the sensor outputs and the command variables, facilitating control system modification for specific applications. The results of two learning experiments using a General Electric P-5 manipulator are presented. The first involved learning to use the video image feedback to position the robot hand accurately relative to stationary objects on a table, assuming no knowledge of the robot kinematics or camera characteristics. The second involved learning to use video image feedback to intercept and track objects moving on a conveyor. In both experiments, control system performance was found to be limited by the resolution of the sensor feedback data, rather than by control structure limitations.

Elevator system having microprocessor-based door operator

Abstract: An elevator system has a door operator with a door operator motor and a dedicated microprocessor for storing door open and door close cycles. The microprocessor initiates door open and close cycles responsive to external door open and door close commands. Preferably the microprocessor stores a plurality of door closed cycles in which the elevator controller selects one of the cycles when issuing a door closed command.

Comparing fuzzy logic with classical controller designs

Abstract: A unified approach for comparing the performance of fuzzy and nonfuzzy controller designs is presented. Relationships are established between the gain parameters for the two classes of controller designs. The methods presented apply equally well to proportional-plus-integral, linear multiband, and multilevel relay controllers.

Implications of large RGA elements on control performance

Abstract: Large elements in the RGA imply a plant which is fundamentally difficult to control. (1) The plant is very sensitive to uncorrelated uncertainty in the transfer matrix elements. (2) The closed-loop system with an inverse-based controller is very sensitive to diagonal input uncertainty. With a diagonal controller, the system is not sensitive to diagonal input uncertainty, but the controller does not correct for the strong directionality of the plant and may therefore give poor performance even without uncertainty.

Adaptive feedback control

Abstract: Adaptive control is now finding its way into the marketplace after many years of effort. This paper reviews some ideas used to design adaptive control systems. It covers early ideas which primarily attempt to compensate for gain variations and more general methods like gain scheduling, model reference adaptive control, and self-tuning regulators. It is shown that adaptive control laws can be obtained using stochastic control theory. Techniques for analyzing adaptive systems are discussed. This covers stability and convergence analysis. Issues of importance for applications like parameterization, tuning, and tracking, as well as different ways of using adaptive control are also discussed. An overview of applications which includes feasibility studies as well as products based on adaptive techniques concludes the paper.

An approach to structure/control simultaneous optimization for large flexible spacecraft

Abstract: This paper presents an approach to the simultaneous optimal design of a structure and control system for large flexible spacecrafts based on realistic objective function and constraints The weight or total cost of structure and control system is minimized subject to constraints on the magnitude of response to a given disturbance involving both rigid-body and elastic modes A nested optimization technique is developed to solve the combined problem As an example, simple beam-like spacecraft under a steady-state white-noise disturbance force is investigated and some results of optimization are presented In the numerical examples, the stiffness distribution, location of controller, and control gains are optimized Direct feedback control and linear quadratic optimal controls laws are used with both inertial and noninertial disturbing force It is shown that the total cost is sensitive to the overall structural stiffness, so that simultaneous optimization of the structure and control system is indeed useful

Security control system

Abstract: A security and control system for use in a home or building which utilizes a coded audio link between the entry detectors/transmitters and the relay modules, and a digital pulse coded power line communication ("PLC") link between the relay modules and the system controller as well as between the system controller and the various remotely located slave units which control the energization of lamps, appliances, and alarms. The relay modules and controller include constant false alarm rate ("CFAR") receivers for isolating the coded audio signal from background noise and unique exclusion circuitry for decoding the isolated signal. The PLC messages are generated by impressing a pulse code modulated high frequency carrier signal onto the AC line at selected points in the AC waveform. The location of each carrier frequency pulse relative to the 60 Hz AC line cycle determines the digital value of the pulse. Both before and during a PLC message transmission, the controller and relay modules are adapted to check the status of the AC power line for the presence of intelligence or excessive noise levels and delay transmission if either condition is detected. In the security mode, the system has three major states: INSTANT-ARM, ARM-DELAY, and DISARM. In the INSTANT-ARM state, the system responds immediately to the detection of an intrusion event. In the ARM-DELAY state, a 40-second delay is implemented before alarm action is taken to permit an authorized entrant to DISARM the system. Significantly, the 40-second delay is implemented by each of the remotely located slave modules so that destruction of the controller by an intruder within the 40-second period will not defeat the system.

Suboptimal control of linear systems with state and control lkequality constraints.

Abstract: A suboptimil controller based upon on-line quadratic programming is described. Theoretical results are presented to show that such a controller is optimal under the assumption that there are no constraints on the Computation time. Finally, an implementation of a suboptimal controller that takes such constraints into account is described.

Design of dynamic control of two cooperating robot arms: Closed chain formulation

Abstract: In this paper the dynamic equation describing two cooperating robot arms which simultaneously are working on the same object is established by considering the whole system as a closed kinematic chain. This formulation has the advantage of automatically handling the coordination and load distribution between the robot arms through the dynamic equation. It can also be generalized to a multi-robot arm system. The control problem is solved as a design problem for a linear system by first applying a nonlinear feedback and nonlinear coordinate transformation to linearize the nonlinear dynamic equation, and then employing the linear optimal control theory to design a robust controller in the task space. This new dynamic control method establishes a direct control response to task space commands facilitating dynamics based task encoding in robotics.

Suboptimal control of linear systems with state and control inequality constraints

Abstract: A suboptimal controller based upon on-line quadratic programming is described. Theoretical results are presented to show that such a controller is optimal under the assumption that there are no constraints on the computation time. Finally, an implementation of a suboptimal controller that takes such constraints into account is described.

Experimental evaluation of feedforward and computed torque control

Abstract: Trajectory tracking errors resulting from the application of various controllers have been experimentally determined on the MIT Serial Link Direct Drive Arm. The controllers range from simple analog PD (proportional-derivative) control applied independently at each joint to feedforward and computed torque methods incorporating full dynamics. It was found that trajectory tracking errors decreased as more dynamic compensation terms were incorporated. There was no significant difference in trajectory tracking performance between the feedforward controller using independent digital servos and the full computed torque controller. Implementing the model-based controller highlights the need for accurate control of joint torque, accurate joint position and velocity sensing, and adequate sampling rates. >

Positive position feedback control for large space structures

Abstract: A new technique for vibration suppression in large space structures is investigated in laboratory experiments on a thin cantilever beam. This technique, called Positive Position Feedback, makes use of generalized displacement measurements to accomplish vibration suppression. Several features of Positive Position Feedback make it attractive for the large space structure control environment: The realization of the controller is simple and straightforward. Global stability conditions can be derived which are independent of the dynamical characteristics of the structure being controlled, i.e., all spillover is stabilizing. The method cannot be destabilized by finite actuator dynamics, and the technique is amenable to a strain-based sensing approach. The experiments control the first six bending modes of a cantilever beam, and make use of piezoelectric materials for actuators and sensors, simulating a piezoelectric active-member. The modal damping ratios are increased by factors ranging from 2 to 130.

Stability analysis of an adaptive controller for robotic manipulators

Abstract: The stability analysis of an adaptive control scheme for robotic manipulators, originally introduced by Horowitz and Tomizuka (1980), is presented in this paper. In the previous stability proof it was assumed that the manipulator parameter variation is negligible compared with the speed of adaptation. It is shown that this key assumption can be removed by introducing two modifications in the adaptive control scheme: 1. Reparametrizing the nonlinear terms in dynamic equations as linear functions of unknown but constant terms. 2. Defining the Coriolis compensation term in the control law as a bilinear function of the manipulator and model reference joint velocities, instead of a quadratic function of the manipulator joint velocities. The modified adaptive control scheme is shown to be globally asymptotically stable.

Data display system.

Abstract: A data display system in which input-output display devices are connected to a central processor, and users select application programs that are run on the central processor. The control system of the central processor includes a display manager control system and a windowing control mechanism which allows a plurality of tasks to be performed concurrently and the results displayed in areas of a display screen. The windowing control mechanism includes, a task manager control program which runs as an application in the display manager control system and includes means to interact, via the display manager, with the operator to allow applications to be initiated, means to create tasks to control the processing of the application in such a way that the applications can be suspended or resumed according to whether the operator is ready for them, and means to identify to the display manager a coordination controller that the display manager can call to allow the task manager to suspend and resume applications. The display manager includes, means to combine data from each application and build a display representation that shows many windows into the various applications onto a single screen, and means to call the coordination controller identified by the task management application so that the task manager can suspend applications that are waiting for input and resume those applications which have input available.

Optimal Efficiency Control of an Induction Motor Drive

Abstract: This paper describes a practical method for achieving optimal efficiency over the complete operating range of a variable speed drive. The proposed system adaptively adjusts the flux level in the motor based upon a direct measurement of the power input to the drive. An internal field orientation torque control loop and a speed regulator are employed to maintain the load speed requirements. Experimental results describing the efficiency optimization and the dynamic behavior of the drive at reduced flux are presented. The influence of the tuning of the field oriented controller on the efficiency of the drive is experimentally investigated.

Extending H-infinity Control to Nonlinear Systems: Control of Nonlinear Systems to Achieve Performance Objectives

Abstract: H-infinity control originated from an effort to codify classical control methods, where one shapes frequency response functions for linear systems to meet certain objectives. H-infinity control underwent tremendous development in the 1980s and made considerable strides toward systematizing classical control. This book addresses the next major issue of how this extends to nonlinear systems. At the core of nonlinear control theory lie two partial differential equations (PDEs). One is a first-order evolution equation called the information state equation, which constitutes the dynamics of the controller. One can view this equation as a nonlinear dynamical system. Much of this volume is concerned with basic properties of this system, such as the nature of trajectories, stability, and, most important, how it leads to a general solution of the nonlinear H-infinity control problem.

A Microprocessor-Based Robot Manipulator Control with Sliding Mode

Abstract: The application of a sliding-mode control based on a Variable Structure System (VSS) for a multijoint manipulator is presented. The high-gain effect of a sliding-mode control suppresses the complicated interactions between each joint of a robot arm. The resulting system is completely robust whereas the obtained control law is simple and easy to apply to on-line computer control. In this-paper, the practical sliding-mode controller, which has a simple nonlinear compensator and proper continuous function, is implemented for a two-linkage manipulator. The validity of this technique is confirmed in experiments where the system shows robust performance in spite of the existing nonlinear interactions and unknown parametric changes. In addition, this sliding-mode control is improved to track the desired path.

Process control system with action logging

Abstract: An integrated system for process control in which a process supervisor procedure defines parameters for one or more controller systems (or control procedures). The supervisor procedure changes control parameters only in discrete changes, and the decision to act is sufficiently constrained that every change must be a significant change. Every change is logged (or otherwise reported out to human experts). Since every change is significant, the history of changes will provide a meaningful record which can be reviewed by human experts.