An Evaluation of Several Controller Synthesis Methodologies Using a Rotating Flexible Beam as a Test Bed

An online delay estimation algorithm is adopted for the adaptive Smith predictor in the networked control systems (NCS) design under the significant delay time. However, the Smith predictor is sensitive to parameter uncertainties within the system model and time delay. The quantitative feedback theory (QFT) controller is suitable to cope with parameter uncertainties of the Smith predictor in this paper; moreover, a template expressed in phase and gain for the QFT design has been constructed by considering the bounded variations with the time delay and the external loading. Therefore, the adaptive Smith predictor control scheme with QFT controller provides better tolerance to parameter uncertainties. Both simulation and experimental results on AC servo motor with both the hybrid controller area network (CAN) bus and the Ethernet network have proven the feasibility and improved performance of the proposed NCS.

Loop shaping is the principle step for synthesising the quantitative feedback theory (QFT) based robust controllers. The controller assures performance robustness in the presence of plant uncertainties. This paper explores a template and bounds free approach for the automated synthesis of low order fixed structure QFT controller for a highly uncertain pneumatic servo actuator system. In this work, the loop-shaping problem has been posed as a multi-objective optimisation problem and solved using the multi-objective variant of the genetic algorithm. At the end of the design process, a set of Pareto optimal solutions (POS) are obtained, to aid the decision maker in choosing an ideal solution from the POS, use of level diagrams has been explored. The simulation of the results and time and frequency domain analysis has been carried out using MATLAB and the results obtained clearly unveil that the designed QFT controller offers robust behaviour over a range of plant's parametric uncertainty.

Automated synthesis of multivariable QFT controller using interval constraint satisfaction technique

The load frequency control (LFC) problem has been one of the major subjects in electric power system design and operation. LFC is becoming much more significant today in accordance with increasing size, changing structure and complexity in interconnected power systems. Practice LFC systems use simple proportional-integral (PI) controllers, but parameters of PI controllers are usually tuned based on the trial-and-error approaches and they are incapable to obtain good dynamic performance under a wide range of operating conditions. For this problem, in this paper quantitative feedback theory (QFT) method is used for LFC problem. A multi-area electric power system with a wide range of parametric uncertainties is given to illustrate proposed method. To show effectiveness of proposed method, a classical PI type controller optimized by genetic algorithms (GA) is designed to compare with QFT controller. The simulation results visibly show the validity of QFT method in comparison with traditional method. Key words: Multi-area electric power system, electric power system load frequency control, robust control, quantitative feedback theory method.

Natural vibration analysis of plates represents an important issue in engineering applications. In this paper, a new and simplify method for vibration analysis of circular and rectangular plates is presented. The design of an effective robust controller, which consistently attenuates transverse vibration of the plate caused by an external disturbance force, is given. The dynamics of the plate is modeled as a distributed parameter system. We have studied the control vibration of the plate using quantitative feedback theory method by determining the transfer functions between various factors of control system. In this method we have developed the general distributed parameter system method for uncertainty problem for simply supported rectangular plate and clamped circular plate. The quantitative feedback method is one of the robust control methods which is capable to solve problems despite structural and non-structural uncertainty. Quantitative Feedback Theory introduces the new technique to design one-point feedback controllers for distributed parameter systems. The results demonstrate that the control law provided a significant reduction in the plate vibration. The numerical simulation of the designed controller demonstrates that the QFT controller can consistently attenuate the vibration compared to a passive system.

This paper proposes a robust controller for semi-active suspension system with actuator dynamics using the quantitative feedback theory. It solves the vehicle vibration attenuation problem using the novel cascade approach. The proposed cascade quantitative feedback theory control approach consists of the inner and outer loop. The damping force tracking of the magneto-rheological damper is chosen as the inner loop, while the outer loop is for the vibration attenuation. The inner loop is added to the control structure to enhance damping force tracking capabilities. The damping force of the magneto-rheological damper depends on the many factors, such as the complex and nonlinear (hysteresis) dynamics and operating temperature. The actuator (magneto-rheological damper) dynamics is well approximated by a first-order model with an uncertain time constant which captures the essential dynamics. The simulation case study is conducted on a realistic quarter car suspension system to show the effectiveness of the proposed cascade control method. The proposed method is found to deliver superior performances, in terms of ride comfort and road holding, over the skyhook, [Formula: see text] control, and single-loop quantitative feedback theory control under the bump, sine, and random road disturbances.

Automated Synthesis of Fixed Structure QFT Controller using Interval Constraint Satisfaction Techniques

This paper investigates an active front steering control strategy based on quantitative feedback theory (QFT). By incorporating feedback from a yaw rate sensor into the active steering system, the control system improves the dynamic response of the vehicle. The steering response of a vehicle generally depends upon uncertain quantities like mass, velocity, and road conditions. Thus, QFT is used to design a controller with robust performance. A multi-degree-of-freedom nonlinear model is co-simulated here by MATLAB Simulink and ADAMS/CAR. The performance of the control system is evaluated under various emergency maneuvers and road conditions. The result shows that the designed robust control system has good control performance and can efficiently improve handing qualities and stability characteristics.

On quantitative feedback design for robust position control of hydraulic actuators

This paper introduces a new analytical formulation to describe the robust performance and stability bounds for the quantitative feedback theory (QFT) controller design methodology. The new approach explicity defines a family of curves that allow the user to significantly reduce the computational effort and improves the accuracy of the design. The paper includes two examples to clarify and validate the analytical formulation.

In the present paper, a non-diagonal multi-input multi-output (MIMO) Quantitative Feedback Theory (QFT) controller design methodology is applied to control the lateral and yaw motions of a car equipped with four-wheel steering. The overall objective is to track the sideslip angle and yaw-rate with the aim of achieving satisfactory performance specifications for the vehicle lateral dynamics, regarding the rejection of external disturbances on yaw rate and sideslip angle, minimizing the interaction as much as possible and taking into account the model uncertainty.

In this work a digital robust controller is designed via Quantitative Feedback Theory (QFT) to maintain a constant cutting force in the presence of parametric uncertainty for a time varying end milling process. The QFT controller is designed using the delta transform method for discrete systems. The controller is designed to limit the overshoot and settling time of the cutting force levels over a range of cutting parameters. Models are presented for the cutting process and machine dynamics including parametric uncertainty, and these models are used to develop a controller which meets given tracking and regulation specifications for all plant values. Good experimental results are obtained by implementing the controller on a high speed milling machine.

Sudden changes in a greenhouse environment negatively impact the development and production of crops, especially in greenhouses with natural ventilation when temperatures are low at night and change rapidly due to wet winds. To mitigate these variations, a design of a robust controller based on Quantitative Feedback Theory (QFT) as from a Smith predictor structure for the dead-time system is proposed. This structure offers high stability based on the gain margin, the phase margin, and the rejection of disturbances in the system output. This design was contrasted with a PID controller based on performance indices, according to the transient response and error in the presence of changes in the point of operation and charge disturbances. Final results showed that the dynamic response of the QFT controller improved compared to PID controller results.

An active disturbance rejection control design for the distillation process with input saturation via quantitative feedback theory

This paper utilizes the quantitative feedback theory (QFT) to design a robust controller for adaptive cutting feedrate control. The proposed algorithm could dynamically change the feedrate according to the spindle current which is highly related to the measured cutting force. The QFT controller could provide the constant cutting force even under different cutting condition. Hence, the machining efficiency could be improved under the robust control. Numerical simulations are conducted to validate the performance of the proposed robust cutting feedrate control algorithm (RFC).