Model Control Structure Research Articles

Controller design for high-frequency cutting using a piezo-driven microstage

Controller design consists of a feedforward and a feedback controller to support a microstage with flexure hinge structure driven by piezoelectric ceramic actuator for high-frequency nanoscale cutting is developed in this article. The feedforward controller is designed based on a hysteresis dynamic model in order to reduce the nonlinear hysteresis effect of piezoelectric actuator. The position feedback controller is designed based upon an exponentially weighted moving average (EWMA) method embedded in an internal model control (IMC) structure constructing a run-to-run IMC (RtR-IMC) control scheme in order to deal with system bias or modeling inaccuracy. Also, disturbance due to temperature rise will influence actuator's performance, hence an additional compensator is included in the IMC structure. Surfaces dimple micro-machining utilizes piezoelectric-driven microstage for high-speed cutting is selected as an example to investigate system performance. The developed control algorithm is implemented on a DSP-based system to provide 1 kHz operating speed. In experiment, the proposed feedforward and feedback controller is verified to be able to overcome those negative factors efficiently and preserve good positioning accuracy.

Type-2 Fuzzy Model Inverse Controller Design Based on BB-BC Optimization Method

AbstractThe use of inverse system model as a controller might be an efficient way in controlling nonlinear systems. It is also a known fact that type-2 fuzzy models can represent nonlinear systems better than type-1 fuzzy models. Therefore, an inverse type-2 fuzzy model can be used as a controller for controlling processes with nonlinearities and/or uncertainties. In the case of uncertainties and/or disturbances, an inverse type-2 fuzzy model based nonlinear internal model control structure is proposed to compensate these errors.

Step Response Identification under Inherent-Type Load Disturbance with Application to Injection Molding

Motivated by autotuning of injection velocity in an industrial injection molding machine, a step response identification method is proposed for practical application subject to inherent-type load disturbance. Both models of the process and the inherent-type load disturbance can be simultaneously derived from a step test. Identification algorithms are detailed for obtaining the widely used low-order models of first-order plus dead time (FOPDT) and second-order plus dead time (SOPDT). Based on the identified process and disturbance models, a two-degree-of-freedom (2DOF) internal model control (IMC) structure plus feed-forward control is proposed for improving load disturbance rejection. Analytical controller design formulas and tuning guidelines are developed accordingly. A practical application to the velocity control of an injection molding machine is shown to illustrate the effectiveness and merits of the proposed identification method and control strategy.

Smith Predictor-Based Control Schemes for Dead-Time Unstable Cascade Processes

This paper presents two simple and efficient Smith predictor (SP) based control schemes which can be used to control open-loop stable or unstable time-delay cascade processes. The proposed structures have two control loops, a secondary inner loop and a primary outer loop. Similar to previous approaches, the secondary loop uses an internal model control (IMC) structure. Two different schemes are proposed for the outer loop that has an unstable open-loop behavior. Contrary to previous proposed controllers, where a delayed model should be used in the stabilization and tuning procedure by considering some kind of polynomial approximation of the dead time, in the proposed structures, internal stability is naturally achieved through a suitable implementation and tuning of the controller without using any delay approximation. To illustrate this, simulation comparative results with some of the schemes recently presented in the literature are presented, showing the simplicity of the proposed design. Moreover, the simulations show that the proposed schemes allow one to obtain some improvement in disturbance rejections performance.

Adaptive Internal Model Control with fractional order parameter

AbstractIn this paper we have introduced as a model in the adaptive Internal Model Control (IMC) structure a fractional order system to obtain a fractional adaptive IMC scheme. We have shown that this adaptive control scheme always provides theoretical guarantees of stability when a stable fractional order transfer function is used as an IMC parameter and that the use of this fractional IMC parameter can improve the performances of the control system along with its robustness against noises. A comparative simulation example is given to illustrate the efficiency of the proposed fractional order adaptive control scheme. Copyright © 2010 John Wiley & Sons, Ltd.

Analysis and design of a double two-degree-of-freedom control scheme

Robust analysis and design for a double two-degree-of-freedom (TDF) scheme are discussed in the paper. It is shown that the double TDF scheme is a TDF version of the internal model control (IMC) structure for integrating and unstable processes and retains the property of the IMC structure for stable processes. A robustness measure is proposed assuming that the controlled process has a general uncertainty description. The measure is convenient for comparing the robustness of different control systems and can be used as a guideline for robust tuning. Finally, a TDF-IMC method is proposed to design and tune the parameters of the double TDF scheme to achieve improved robust performance.

Direct design from input/output data of a fault‐tolerant control system based on GIMC structure

AbstractThis paper deals with a method for the design of a fault‐tolerant control system based on the Generalized Internal Model Control (GIMC) structure, consisting of a standard outer loop feedback controller and an extra inner loop controller. The distinguishing feature of the GIMC structure is that controller design for performance and robustness may be performed separately. The outer loop controller is designed for nominal performance using some controller synthesis to meet the (nominal) control specification, while the inner loop controller is designed to make a trade‐off between robustness and performance. This feature is suitable for fault‐tolerant control. The outer loop controller is designed for the fault‐free case, and the inner loop controller for the fault‐time case. In the conventional methods, the inner loop controller is designed to maximize the robust stability margin without fault information. Therefore, the performance in the fault‐time case tends to become conservative. In this paper, the inner loop controller is directly designed from experimental data collected from the faulty system. Since the collected data contains information on the fault, conservativeness in the conventional methods is decreased. The inner loop controller is designed by Virtual Reference Feedback Timing (VRFT). VRFT is a method of direct design from input‐output data without identifying any models. Since the complexity of the controller can be specified by the designer, no complexity reduction is necessarily required, which is advantageous in implementation. The effectiveness of the proposed design method is confirmed by an experiment. © 2010 Wiley Periodicals, Inc. Electr Eng Jpn, 171(4): 53–62, 2010; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/eej.20929

IMC-based iterative learning control for batch processes with uncertain time delay

Based on the internal model control (IMC) structure, an iterative learning control (ILC) scheme is proposed for batch processes with model uncertainties including time delay mismatch. An important merit is that the IMC design for the initial run of the proposed control scheme is independent of the subsequent ILC for realization of perfect tracking. Sufficient conditions to guarantee the convergence of ILC are derived. To facilitate the controller design, a unified controller form is proposed for implementation of both IMC and ILC in the proposed control scheme. Robust tuning constraints of the unified controller are derived in terms of the process uncertainties described in a multiplicative form. To deal with process uncertainties, the unified controller can be monotonically tuned to meet the compromise between tracking performance and control system robust stability. Illustrative examples from the recent literature are performed to demonstrate the effectiveness and merits of the proposed control scheme.

A Solution to the Accuracy/Robustness Dilemma in Impedance Control

<para xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> It has been reported that, in impedance control, there exists a dilemma between impedance accuracy and robustness against modeling error. As a solution to this dilemma, an accurate and robust impedance control technique is developed based on internal model control structure and time-delay estimation: the former injects desired impedance and corrects modeling error, the latter estimates and compensates the nonlinear dynamics of robot manipulators. Owing to the simple structure, the proposed control is designed without requiring entire model computation or complex algorithms. In 2-DOF SCARA-type robot experiments, the accuracy and robustness of the proposed control are confirmed through comparisons with other competent controllers including impedance control with disturbance observer. </para>

Gain-scheduled model-based feedback control of the air/fuel ratio in diesel engines

This paper investigates the adoption of an innovative closed-loop control of the air/fuel ratio (AFR) in modern diesel engines. The in-cylinder AFR is in fact a critical quantity responsible for the formation of NO x and particulate matter emission. Two approaches are investigated for the design of a gain-scheduled AFR controller, that are based on the internal model control structure and on the H ∞ design method. In addition, two feedforward controllers are investigated for improving the tracking quality of the system. In terms of tracking performance and driveability, the proposed AFR controllers at least match the series production EGR controller. However, due to the fact that an AFR controller uses information obtained after the combustion process, it can also deal with the drift of sensors and actuators involved in the control loop.

Uncertainty analysis and robust control of temperature fields of casting mould as distributed parameter systems

In the paper, an uncertainty analysis and simulation of a robust control of temperature fields of the casting mould in the benchmark casting plant are presented. Temperature fields are supposed as distributed parameter systems with dynamic models in the form of lumped-input/distributed-output system. For this representation, uncertainty of the controlled system was considered and robust control synthesis with internal model control structure was designed. Simulation of the robust control of the temperature field in the casting mould was carried out using the Distributed Parameter Systems Blockset for MATLAB & Simulink – Third-party MathWorks product.

Identification and Robust Control of DC/DC Converter Hammerstein Model

This paper deals with model-based robust control of DC/DC power electronic converters. The converter is described by means of a Hammerstein model consisting of the nonlinear static characteristics of the converter and a linear time-invariant (LTI) uncertain model whose parameters depend on the actual duty-cycle operating range. This suggests that the controller be designed using robust control techniques. In view of applying robust control, identification of the earlier LTI models is performed by means of simulation experiments, carried out on a converter switching model implemented on MATLAB/SIMULINK environment. Internal model control (IMC) structure is employed for the controller design, but its implementation is performed using the equivalent feedback control structure. Comparison with some controllers designed starting from models that do not require identification steps is performed with the aim of showing the advantages connected to the availability of a suitable model, which describes the essential aspects of the behavior of the system, for control purposes. Comparison with a PI controller designed by means of phase margin assignment is carried out with the aim of justifying the use of more sophisticated control methods. Experimental results are also shown that aimed to prove the validity of the whole approach. Comparison of experimental and simulation results is also performed.

A feedforward IMC structure for controlling the charging temperature of a TES system of a solar cooker

A feedforward internal model control (IMC) structure for controlling and maintaining the outlet charging temperature of a thermal energy storage (TES) system of a solar cooker is presented. The TES system consists of a packed pebble bed in thermal contact with a heat transfer oil contained in a storage tank. An electrical hot plate simulates the collector/concentrator which heats up the oil circulating in a hollow copper spiral coil thus charging the storage. A model for the collector/concentrator system is developed to enable simulation of the feedforward IMC structure. Using a Simulink block model, the simulation results reveal that a feedforward IMC structure performs better than a feedforward structure. The feedforward IMC structure is tested experimentally and the performance of the control structure is acceptable within a few degrees of the set temperatures. Experimental results are also compared with the simulation results. The simulated responses are found to relate closely to the experimental ones and any discrepancies between the two are discussed. Furthermore, the feedforward IMC structure is also compared experimentally with a combined feedforward and PID feedback structure. Results of the comparison indicate that the feedforward IMC structure performs better than the combined feedforward and PID feedback structure. The thermal profile of the storage during the charging experiment with the feedforward IMC structure is also presented and the results obtained from the storage profile indicate that the storage tank is thermally stratified.

Closed-Loop Control and Advisory Mode Evaluation of an Artificial Pancreatic β Cell: Use of Proportional-Integral-Derivative Equivalent Model-Based Controllers

Using currently available technology, it is possible to apply modern control theory to produce a closed-loop artificial beta cell. Novel use of established control techniques would improve glycemic control, thereby reducing the complications of diabetes. Two popular controller structures, proportional-integral-derivative (PID) and model predictive control (MPC), are compared first in a theoretical sense and then in two applications. The Bergman model is transformed for use in a PID equivalent model-based controller. The internal model control (IMC) structure, which makes explicit use of the model, is compared with the PID controller structure in the transfer function domain. An MPC controller is then developed as an optimization problem with restrictions on its tuning parameters and is shown to be equivalent to an IMC controller. The controllers are tuned for equivalent performance and evaluated in a simulation study as a closed-loop controller and in an advisory mode scenario on retrospective clinical data. Theoretical development shows conditions under which PID and MPC controllers produce equivalent output via IMC. The simulation study showed that the single tuning parameter for the equivalent controllers relates directly to the closed-loop speed of response and robustness, an important result considering system uncertainty. The risk metric allowed easy identification of instances of inadequate control. Results of the advisory mode simulation showed that suitable tuning produces consistently appropriate delivery recommendations. The conditions under which PID and MPC are equivalent have been derived. The MPC framework is more suitable given the extensions necessary for a fully closed-loop artificial beta cell, such as consideration of controller constraints. Formulation of the control problem in risk space is attractive, as it explicitly addresses the asymmetry of the problem; this is done easily with MPC.

ＧＩＭＣ構造による故障検出とその磁気浮上システムへの応用

This paper deals with a fault detection for a magnetic suspension system by using Generalized Internal Model Control (GIMC) structure. To design a robust fault detection filter, fault detection design problems are formulated as multiple objective optimization problems by minimizing the effects of disturbances and keeping the fault sensitivity involving an LTI system with disturbance and fault signals. The designed fault detection filters by solving each optimization problems are implemented with the magnetic suspension system to verify its validity. In experimental results, the sensor fault is detected by the designed filter. Moreover, the disturbance affection is more reduced than the detection system using the conventional detection filter.

GIMC-based Fault Detection and Its Application to Magnetic Suspension System

Abstract This paper deals with a fault detection for a magnetic suspension system by using Generalized Internal Model Control (GIMC) structure. To design robust fault detection filters, two fault detection design problems are formulated as multiple objective optimization problems by minimizing the effects of disturbances and maximizing the fault sensitivity involving an LTI system with disturbance and fault signals. The fault detection filters designed by solving each optimization problems are implemented with the magnetic suspension system to verify its validity. A filter designed via the problem 1 has good transient performance, but the output signal of the filter is affected by the disturbance signals. Another filter which is designed via the problem 2, however, has good robustness for disturbance signals. Moreover, experimental results show that both filters have enough fault detection properties compared with a conventional detection filter.

Robust Output Feedback of Minimum Phase Nonlinear Systems

A robust output feedback controller is synthesized for minimum phase multivariable nonlinear systems based on thedifferential geometry approach. Using the internal model control structure within the input-output (I/O) linearizationframework, the controller is combined with a closed-loop observer to estimate transformed states in the outer-loop. It isshown that the controller-observer combination achieves robust tracking and estimation using simple tuningparameters. The effectiveness of the proposed system is illustrated by a simulation example for control of concentrationin a chemical reactor.

Nonlinear Internal Model Control of Diesel Air Systems

As a result of the increased complexity of today's power trains, the traditional ways of designing engine control systems essentially through ad hoc methods and experimental tuning will no longer provide the desired level of performance. In this paper, a novel model-based controller is described which accommodatesmany of today's demands on controller development of the automotive industry. The control problem treated here is a boost pressure control of a turbocharged diesel engine with a variable nozzle turbine (VNT). Since the system is essentially nonlinear, a robust nonlinear controller is used. The tracking problem is treated by a control method which combines the Internal Model Control (IMC) structure with the flatness-based approach to design feedforward controllers. The main idea of IMC is to include the model of the plant into the feedback controller. If the model perfectly represents the plant and no disturbances occur, the IMC structure degenerates to a pure feedforward control. Flat systems are characterized by the fact that their input can be expressed explicitly in terms of internal system dynamics which results in a simple method for designing a feedforward controller. In order to extend this concept to nonlinear systems, a flatness-based feedforward controller is proposed as IMC controller. Furthermore, the introduced method allows to explicitly consider input constraints. It is shown that this new concept provides an efficient controller design for certain nonlinear systems and ensures robustness and offset-free tracking. Simulation and testbed results of a controlled air system of a turbocharged diesel engine demonstrate the feasibility of this control scheme which results in impressive control performance.

Robustly Stable Control of Continuous-time Generalized Predictive Control Combined with QFT Based on GIMC Structure

The continuous-time generalized predictive control (CGPC) and the quantitative feedback theory (QFT) are used together to control the plant with high uncertainty. QFT conquers the plant uncertainty and stabilizes the system in the inner loop without affecting the nominal performance based on the generalized internal model control (GfMC) structure. CGPC is used to obtain the necessary control performance in the outer loop. According to several given sufficient conditions, the available tuning parameters of CGPC are selected to make the system robustly stable. Finally, an example is given to show how to use this technique; and it is shown that this combined approach gets better performance than if only one of them is used.

Fuzzy Feedback Linearizing Controller and Its Equivalence With the Fuzzy Nonlinear Internal Model Control Structure

Fuzzy Feedback Linearizing Controller and Its Equivalence With the Fuzzy Nonlinear Internal Model Control StructureThis paper examines the inverse control problem of nonlinear systems with stable dynamics using a fuzzy modeling approach. Indeed, based on the ability of fuzzy systems to approximate any nonlinear mapping, the nonlinear system is represented by a Takagi-Sugeno (TS) fuzzy system, which is then inverted for designing a fuzzy controller. As an application of the proposed inverse control methodology, two popular control structures, namely, feedback linearization and Nonlinear Internal Model Control (NIMC) are investigated. Moreover, the paper points out that, under some conditions, both of the control structures are equivalent and naturally implement a Smith predictor in the presence of time delays.