Model-following Control Research Articles

Development of an automatic arc welding system using a variable structure model reference scheme

This paper presents an automatic welding control system for the alternating current shield metal arc welding process. A nominal nonlinear mathematical model containing uncertainties such as dead-zone, welding control system saturation, and the identified system parameters is derived. A novel variable structure model reference control scheme is designed to modulate the rate of the electrode feed mechanism, thereby regulating the arc current. The developed controller assures the global reaching condition of the sliding mode of the controlled welding system. In the sliding mode, the electric current error between the plant and the model asymptotically approaches zero. Moreover, the welding system remains insensitive to uncertainties and disturbance as the systems with friction. The simulation and experimental results confirm that the automatic welding control system, based on the proposed model-following variable structure controller, successfully maintains the magnitude of the arc current at the desired value and preserves the stability of the arc length, thereby ensuring excellent welding performance.

Hybrid model-based force/position control: theory and experimental verification

Force/position control is a relatively young and rapidly developing branch of robotics. Its practical implementation faces many difficulties due to inherent process complexity. Despite this, the majority of contributions in this field use the classic approach to force control, i.e. single-loop PID control. In this paper, two model-based control structures are proposed, yielding much better results of force control as compared to the classic approach, to be achieved. These are two-loop model-following control (MFC) structures that guarantee interesting disturbance suppression behaviour by an additional degree of freedom. Tests carried out with a Manutec r2 manipulator with six degrees of freedom have shown clear advantages of the control structures under study.

Direct Self-Tuning Model-Following Control with Integral Action for a Variable-Frequency Oil-Cooling Process

This paper presents a direct self-tuning model-following control with integral action for a variable-frequency oil-cooling process, suitable for cooling down high-speed machine tools. The oil-cooling process is experimentally modelled as a first-order system with a given time-delay Based on this model, a direct self-tuning model-following control with integral action is proposed for achieving set-point tracking and disturbance rejection. A real-time adaptive predictive control algorithm is then presented and implemented utilizing a standalone digital signal processor (DSP). In comparison with the control method of Tsai and Huang, the proposed method provides a more practical and less computationally intensive approach for achieving the desired high-precision set-point tracking and disturbance rejection. Experimental results show that the proposed control method is capable of giving a satisfactory set-point tracking performance under set-point changes, fixed loads, and load changes.

Low power consumption focusing actuator for a mini video camera

A novel low power consumption autofocusing actuator in a mini video camera is constructed in accordance with the result of a systematic design procedure of voice coil motors (VCM). This paper emphasizes the position control of such a VCM. The position feedback signals are provided by a magnetoresistive (MR) encoder. The position estimation algorithm (PEA) is developed to precisely decode the MR signals for the position of the moving part of the VCM. Different postures change the loading of the moving part of the VCM, so that an adaptive model-following control system based on the PEA is proposed to compensate for the loading variation. The experiments verify the fast dynamic performance and high power efficiency of the VCM.

Simple two degree of freedom structures and their properties

A two-degree of freedom control system that is most frequently encountered in practice is the so-called Internal Model Control (IMC) structure. However, the design procedure of such a structure does not present an easy task, which implies a limited utility of IMC. In this paper two alternative solutions are proposed that may be lumped together as Model-Following Control (MFC). These are two-loop control systems being easy to implement and offering interesting properties. Theoretical assumptions have been verified experimentally on a two-joint robot manipulator. Both qualitative and quantitative results yielded by experiments are presented and discussed.

Model-matching control of uncertain continuous-time plants through a feedforward correcting controller

This paper is concerned with the closed-loop robust stability of model-following control schemes for continuous-time linear plants under parametrical uncertainties and/or unmodeled dynamics and possible presence of external disturbances. Apart from the nominal controller, a correcting one is incorporated to improve the disturbance rejection in certain ranges of frequencies adopting the general form of a feed-forward compensator which is also operated by correcting signals taking account the deviation of the nominal system with respect to the current perturbed one. A Bode's type design is utilized to improve the reliability of the proposed scheme. The method is easy to implement and efficient in a variety of practical applications.

ROBUST PID MODEL FOLLOWING CONTROL

The paper deals with properties of the so-called model-following control systems that contain a nominal model of the controlled plant and two PID controllers. An approach to design robust controllers for a SISO process from the viewpoint of its input sensitivity is presented. The proposed structures have been tested by simulation and experiment on linear and nonlinear control plants with perturbed parameters. Results of tests lend support to the view that the proposed structure significantly extends the range of applicability, performance, and robustness of the control system, and thereby eliminates to a large extent the need to employ an adaptation mechanism. Therefore, the structure may find wide application to robust control of plants with time-varying parameters.

A Method for Improving the Robustness of PID Control

In this paper, an effective method is proposed for robust proportional-integral-derivative (PID) control that is easily implementable on commonly used equipment such as programmable logic controller (PLC) and programmable automation controller (PAC). The method is based on a two-loop model following control (MFC) system containing a nominal model of the controlled plant and two PID controllers. Basic features exhibited by the MFC structure are presented, and a technique to tune both component controllers is given. The proposed structures have been implemented in a programmable logic controller and tested on control plants with perturbed parameters. Also, the proposed control system has been checked for its performance in cases when the operation of PID controllers is based on fuzzy logic. Tuning rules for the fuzzy controllers in the presented MFC system have been proposed. Results of tests lend support to the view that the proposed control structures may find wide application to robust control of plants with time-varying parameters.

Adaptive Aircraft Flight Control Simulation Based on an Artificial Immune System

Over the past decade much progress has been made in the development of adaptive, model-following flight control systems. These systems are being designed to account for the degradation and even the failure of the actuators used to implement the control laws within aircraft. Typically, these adaptive, model-following flight control systems require software components capable of (1) monitoring system performance, (2) quantifying changes occurring in the performance characteristics of actuators, and (3) adapting control laws based on changes in actuator performance. Interestingly enough, the challenges facing natural immune systems also require the successful completion of three similar tasks: (1) monitoring organism performance, (2) identification of antigens, and (3) distribution of targeted antibodies. Thus, the characteristics inherent in natural immune systems have been captured and employed in computational systems called artificial immune systems (AISs). This paper describes an adaptive, model-following flight control system based on an artificial immune system. The effectiveness of the approach is demonstrated in a system designed to maintain cruise conditions in the simulation of a Boeing 747 aircraft in the presence of atmospheric turbulence and degradations in the performance characteristics of actuators used to manipulate various control surfaces.

A robust algorithm for model-following control of under-actuated systems, and its application to a non-holonomic robot and an aircraft

In this paper, we present an algorithm for model-following control of under-actuated systems. To make the algorithm robust, we try to suppress computation errors from approximations which are often encountered in the cases of applying the existing algorithms to the under-actuated systems. In this view, we present an algorithm without any kinds of approximations, even in the cases of under-actuated systems. Finally, we check the examples in which the proposed algorithm is applied to a non-holonomic robot and an aircraft.

Improved Electric Arc Furnace Operation Via Implementation of a Geno-Fuzzy Control System

ABSTRACT The U.S. steel industry is growingly increasingly interested in the process of slag foaming in their electric arc furnace plants. Although slag foaming has been shown to improve plant efficiency, this highly dynamic process can be very difficult to consistently control. This article describes a computer control system developed to effectively manipulate the slag foaming process, and the implementation of the controller in an electric arc furnace plant. The control system is a model-following controller based on fuzzy logic. It uses a neural network to simulate the slag foaming process. Furthermore, the control system uses an evolutionary algorithm to effectively tune its fuzzy rule base in response to the dynamic behavior of the slag foaming process. Results are presented, which demonstrate the effectiveness of the control system in this process characterized by relatively slow process dynamics.

Flight Control System Design for Propulsion-Controlled Aircraft

The loss of an aircraft's primary flight controls can lead to a fatal accident. However, if the engine thrust is available, controllability and safety can be retained. This article describes flight control using engine thrust only when an aircraft has lost all primary flight controls. This is a kind of flight control reconfiguration. For safe return, the aircraft must first descend to a landing area, decelerate to a landing speed, and then be capable of precise flight control for approach and landing. For these purposes, two kinds of controllers are required: a controller for descent and deceleration and a controller for approach and landing. The former controller is designed for longitudinal motion using a model-following control method, based on a linear quadratic regulator. The latter is designed by an H∞ state-feedback control method for both longitudinal and lateral-directional motions. Computer simulation is conducted using linear models of the Boeing 747. The results indicate that flight path control, including approach and landing, is possible using thrust only; however, speed control proves more difficult. However, if the horizontal stabilizer is available, the airspeed can be reduced to a safe landing speed.

System Identification for Retrofit Reconfigurable Control of an F/A-18 Aircraft

We summarize a retrofit reconfiguration methodology that augments the production flight control system of an F/A-18 to compensate for changes in aircraft stability and control derivatives caused by aerodynamic control surface failures. The retrofit architecture relies on an indirect-adaptive model-following control approach that exploits onboard models of the closed-loop aircraft dynamics in the control computations. An output-error parameter identification process is used off-line to model the nominal behavior of the F/A-18 inner closedloop (airframe and baseline controller). The identified models are employed to describe the desired behavior for the controller and to provide regularization for an online parameter identification process. The online system identification algorithm updates the parameters of the models used for control decision, and a regularized recursive least-squares method is chosen to enable rapid adaptation to unforeseen failures and unmodeled dynamics while being robust to periods of low excitation. The retrofit reconfigurable controller was evaluated in high-fidelity F/A-18 simulations across a wide envelope of flight conditions with single and multiple control surface failures

ROBUSTLY STABLE MODEL-FOLLOWING CONTROL OF UNCERTAIN CONTINUOUS TIME PLANTS WITH THE USE OF A CORRECTING CONTROLLER

ABSTRACT This paper deals with the robust stability of model-following control schemes for linear plants under parametric uncertainties and/or unmodeled dynamics and external disturbances. Apart from the nominal controller, a correcting one is incorporated to improve the disturbance rejection in certain ranges of frequencies. A Bode-type design is proposed to improve the reliability of the proposed method.

Robust model following control of parallel buck converters

A robust model-following (RMF) control technique for average current mode controlled (ACC) parallel buck dc-dc converters, RMFACC, is presented. RMFACC achieves that the loop gain of the voltage loop is little sensitive to the variation of power stage parameters: number of modules, input voltage, load, and component tolerances. The design of the voltage loop is 'decoupled' from the design of the disturbance rejection transfer functions in an important degree, so that the output impedance and audio susceptibility are greatly reduced without the need of high loop gain crossover frequencies. A comparative study between conventional ACC and RMFACC is shown.

Forward-model-based control system for robot manipulators

Although numerous sophisticated nonlinear control algorithms exist in literature, it is still state of the art to use simple linear joint controllers in industrial robotic systems. Most nonlinear concepts are based on a more or less accurate inverse model of the robot. In this paper a forward-model-based control system, the so-called Model Following Control (MFC), for robot manipulators is presented. Its theoretical basics and its concept are explained. The quality and the applicability of the MFC control concept has been analyzed in many experiments. The MFC system is compared with classical linear controllers and nonlinear feedforward controllers with respect to robustness. Qualitative as well as quantitative results are presented and discussed.

外乱収束性能を最適化したモデル追従制御則―ＭｕＰＡＬ‐αの横／方向運動制御への適用とその飛行実験結果―

This paper considers a model-following controller with optimal disturbance attenuation. The controller design process follows a similar approach to the MDM/MDP (Multiple Delay Models/Multiple Design Points) design method, in which the controller performance is evaluated only at selected design points and optimization is performed numerically. Unlike the MDM/MDP method, however, performance is evaluated over the whole range of uncertainties, and is optimized with a method which has a convergence property. In this design process, the performance of the disturbance attenuation is defined as a quadratic cost function and the design problem is formulated with one convex and one non-convex condition, but this is not easily solvable. A design procedure that uses an iterative algorithm, which is easily solvable and has the convergence property, is presented to render the problem tractable. Next, model-following controllers for the lateral/directional motions of MuPAL-α, one of the National Aerospace Laboratory’s flight experiment aircraft are designed with the proposed method, and the results of flight experiments to verify their performances are presented.

Model-Following Controller Based on Neural Network for Variable Displacement Pump.

The variable displacement axial piston pump (VDAPP) is inherently nonlinear, time variant and subjected to load disturbance. The controls of flow and pressure of VDAPP are achieved by changing the swashplate angle. The swashplate actuators are controlled by an electro-hydraulic proportional valve (EHPV). It is reasonable for swashplate angle of a VDAPP to employ neural network based on adaptive control. In this study, the nonlinear model of the VDAPP with a three-way electro-hydraulic proportional valve is proposed, and a neural network model-following controller is designed to control the swashplate swivel angle. The time response for the swashplate angle is analyzed by simulation and experiment, and a favorable model-following characteristic is achieved. The proposed neural controller can conduct nonlinear control in VDAPP, enhance adaptability and robustness, and improve the performance of the control system.

Globoidal cam indexing servo drive control by IVSMFC with load torque estimator

This paper introduces an integral variable-structure model-following control (IVSMFC) incorporated with a load torque estimator based on variable-structure technique for a globoidal cam indexing system. IVSMFC features excellent robustness and performance properties under certain disturbances and parameter variations. However, heavy time-varying load may influence expected performance. In a cam system, when it is in motion, the load produced by inertia forces deflects the driving motor speed and, as a result, degrades the indexing precision. To fulfill the constant driving speed assumption, a load torque estimator is employed and fed forward to compensate the load torque variations. A digital-signal-processor-based globoidal cam indexing servo drive is presented and the experimental results show the effectiveness of the proposed scheme.

A Study on the SELENE-B Model-Following Control System Using the Flying Test Bed.

The future SELENE (SELenological and ENgineering Explorer) mission is planned to make a soft-landing on the lunar surface. The lunar lander is called "SELENE-B." For preliminary terrestrial landing experiments, the flying test bed (FTB) was developed and the first flight experiment finished, which was aimed at validation of the whole FTB flight system. Other experiments are planned for validation of the SELENE-B onboard hardwares, such as sensor systems, and softwares for control systems. In order to validate those systems, it is desirable for the FTB to have the same dynamic characteristics as the SELENE-B. In this paper we are concerned with the controller of the FTB which achieves the SELENE-B model-following system using the FTB. Some numerical simulations are provided to show the effectiveness of the proposed SELENE-B model-following system.