Performance Of Designed Controller Research Articles

L 2-Gain Control for T-S Fuzzy Systems Over an Event-Triggered Communication Network Using Delay Decomposition and Deviation Bounds of Membership Functions

This paper is concerned with networked \(L_2\)-gain control for a T-S fuzzy system over an event-triggered communication network. Taking an event-triggered communication scheme and network-induced delays into consideration, the networked control system is described by an asynchronous T-S fuzzy system with an interval time-varying delay. Due to variation characteristic of network-induced delays, the interval is decomposed into N subintervals and the jumping among these subintervals is governed by a Markov chain. A new relaxation method, which fully utilizes the convexity of normalized membership functions and the deviation bounds of asynchronous normalized membership functions, is proposed and a stochastic Lyapunov–Krasovskii functional is constructed to derive some delay-dependent criteria on \(L_2\)-gain performance analysis and controller design of the asynchronous T-S fuzzy system. An illustrative example is provided to show that the proposed criteria are of less conservatism and less computational complexity than some existing results, and are effective in achieving a prescribed \(L_2\)-gain performance.

A mixed H2/passivity performance controller design for a drum-boiler system

The mixed performance control problem of drum-boiler systems is discussed and investigated in this paper, subject to H2 and passivity performances. In order to minimize output energy and guarantee asymptotical stability, an H2 control scheme is employed to solve the stability problem of system. Passivity theory is applied to achieve disturbance attenuation performance. Based on the Lyapunov function, some sufficient conditions are derived into linear matrix inequality (LMI) form to apply a convex optimization algorithm. Based on the derived sufficient conditions, the asymptotical stability and mixed H2/Passivity performance of the system is achieved by the designed controller. Finally, some simulation results are proposed for a drum-boiler system with external disturbance in order to verify the validity and effectiveness of the proposed design method.

Design and Simulation of Internal Model Controller for a Real Time Nonlinear Process

Background/Objectives: PID controllers are one of the first solutions often considered in the control of process industries. It has always been very difficult to treat the level anomalies n the real time processes. Particularly the non linear systems and processes have been a challenge in relation with their dynamics and flow properties. Methods/Statistical analysis: Dual Spherical Tank Liquid Level System (DSTLLS) has the characteristics of nonlinearity due to the dynamic behaviour and area of cross section of tank. One of the major problems in process industries is to control of liquid level for Second Order System Plus Delay (SOSPD) system because the presence of time delay in the system can lead to destabilization of the system. This simulation aims at portraying the performance of the designed Internal Model Control (IMC) PID Controller. Using the black box modelling technique the SOSPD is mathematically modelled experimentally, assuming the system to be a Single Input Single Output (SISO) model. Findings: The aim of this paper is to design a PID controller using IMC tuning method for a (DSTLLS) whose modelling has been done in real time. This simulation briefly explains about stabilizing problem for SOSPD system using an IMC PID controller. The designed controller performance is analysed in terms of performance indices like Integral Squared Error (ISE) and Integral Absolute Error (IAE) and time domain specifications like Rise time, Settling time and Peak time. Conclusion: The validation of the performance of the designed controller is performed under MATLAB environment. There can different controllers which can be also experimented on the same mathematical model for different configurations of the system, namely MISO and MIMO.

Modelling and control of a shell structure based on a finite dimensional variational formulation

A mathematical model of a controlled shell structure based on Hamilton’s principle and the generalized Ritz–Galerkin method is proposed in this paper. The problem of minimizing the stress energy is solved explicitly for a static version of this model. For the dynamical system under consideration, a procedure for estimating external disturbances and the state vector is derived. We also propose an observer design scheme and solve the stabilization problem for an arbitrary dimension of the linearized model. This approach allows us to perform control design for double-curved shells of complex geometry by combining analytical computation of the controller parameters with numerical data that represent the reference configuration and modal displacements of the shell. As an example, the parameters of our model are validated by results of a finite element analysis for the Stuttgart SmartShell structure.

Signal difference-based deadband H∞ control approach for networked control systems with limited resources

This paper investigates a signal difference-based dead-band H∞ control approach for networked control systems (NCSs) with limited resources. The effects of variable network-induced delays, sampling intervals and data transmitting deadbands are considered simultaneously and the model of the NCS is presented. A Lyapunov functional is adopted, which makes full use of the network characteristic information including the bounds of network delay (BND), the bounds of sampling interval (BSI) and the bounds of transmission deadband (BTD). In the meanwhile, the new H∞ performance analysis and controller design conditions for the NCSs are proposed, which describe the relationship of BND, BSI, BTD and the system's performance. Three examples are used to illustrate the advantages of the proposed methods. The results have shown that the proposed method not only effectively reduces the data traffic, but also guarantees the system asymptotically stable and achieves the prescribed H∞ disturbance attenuation level.

Particle filter algorithms for identification of minimally parametrized Wiener models of drug administration effect

Closed-loop drug administration is performed by a feedback controller keeping the patient response around a pre-set level in the face of process disturbance and uncertainty. To guarantee the safe operating envelope of the closed-loop drug delivery system, controller design for performance and robustness is typically based on a mathematical model of the plant. Minimally parametrized Wiener models comprising a linear dynamic block and a smooth output nonlinearity have been shown to accurately capture the patient-specific pharmacokinetics and pharmacodynamics in closed-loop drug administration. Due to the nonlinear model dynamics, identification techniques based on linear or linearized models yield biased parameter estimates and thus introduce superfluous uncertainty. The present paper compares the performance of three nonlinear system identification algorithms: an extended Kalman filter, a conventional particle filter (PF), and a PF making use of a orthonormal basis to estimate the probability density function from the particle set. A database of patient models estimated under PID-controlled neuromuscular blockade during general anesthesia is utilized, along with the clinical measurements. The bias and variance of the estimated models are related to the computational complexity of the identification algorithms, highlighting the superiority of the PFs in this safety-critical application.

A methodology for identification and control of electro-mechanical actuators

Mechatronic systems are fully-integrated engineering systems that are composed of mechanical, electronic, and computer control sub-systems. These integrated systems use electro-mechanical actuators to cause the required motion. Therefore, the design of appropriate controllers for these actuators are an essential step in mechatronic system design. In this paper, a three-stage methodology for real-time identification and control of electro-mechanical actuator plants is presented, tested, and validated. First, identification models are constructed from experimental data to approximate the plants’ response. Second, the identified model is used in a simulation environment for the purpose of designing a suitable controller. Finally, the designed controller is applied and tested on the real plant through Hardware-in-the-Loop (HIL) environment. The described three-stage methodology provides the following practical contributions:•Establishes an easy-to-follow methodology for controller design of electro-mechanical actuators.•Combines off-line and on-line controller design for practical performance.•Modifies the HIL concept by using physical plants with computer control (rather than virtual plants with physical controllers).Simulated and experimental results for two case studies, induction motor and vehicle drive system, are presented in order to validate the proposed methodology. These results showed that electromechanical actuators can be identified and controlled using an easy-to-duplicate and flexible procedure.

Control and Evaluation Using a Parallel Robot

This article focuses mainly on the parallel manipulator controller design and application of virtual reality technology. Compared to traditional in-line body of parallel mechanism with high precision, high rigidity, width bandwidth and able to load characteristics, such as, in recent years has gradually been applied to robots. Space vector view derivation of parallel mechanism kinematics and inverse kinematics, and speed through the program find the Jacobian matrix, and find the location singular points. Virtual reality (VR) is the main purpose of using the manmachine interface and the interaction between robots. Through human intelligence and sensing device can control in real time to complete complex, heavy or high risk job robot.

Sum-of-squares-based fuzzy controller design using quantum-inspired evolutionary algorithm

In the field of fuzzy control, control gains are obtained by solving stabilisation conditions in linear-matrix-inequality-based Takagi–Sugeno fuzzy control method and sum-of-squares-based polynomial fuzzy control method. However, the optimal performance requirements are not considered under those stabilisation conditions. In order to handle specific performance problems, this paper proposes a novel design procedure with regard to polynomial fuzzy controllers using quantum-inspired evolutionary algorithms. The first contribution of this paper is a combination of polynomial fuzzy control and quantum-inspired evolutionary algorithms to undertake an optimal performance controller design. The second contribution is the proposed stability condition derived from the polynomial Lyapunov function. The proposed design approach is dissimilar to the traditional approach, in which control gains are obtained by solving the stabilisation conditions. The first step of the controller design uses the quantum-inspired evolutionary algorithms to determine the control gains with the best performance. Then, the stability of the closed-loop system is analysed under the proposed stability conditions. To illustrate effectiveness and validity, the problem of balancing and the up-swing of an inverted pendulum on a cart is used.

Reliable gain‐scheduled control design for networked control systems

In this article, the problem of reliable gain‐scheduled H∞ performance optimization and controller design for a class of discrete‐time networked control system (NCS) is discussed. The main aim of this work is to design a gain‐scheduled controller, which consists of not only the constant parameters but also the time‐varying parameter such that NCS is asymptotically stable. In particular, the proposed gain‐scheduled controller is not only based on fixed gains but also the measured time‐varying parameter. Further, the result is extended to obtain a robust reliable gain‐scheduled H∞ control by considering both unknown disturbances and linear fractional transformation parametric uncertainties in the system model. By constructing a parameter‐dependent Lyapunov–Krasovskii functional, a new set of sufficient conditions are obtained in terms of linear matrix inequalities (LMIs). The existence conditions for controllers are formulated in the form of LMIs, and the controller design is cast into a convex optimization problem subject to LMI constraints. Finally, a numerical example based on a station‐keeping satellite system is given to demonstrate the effectiveness and applicability of the proposed reliable control law. © 2014 Wiley Periodicals, Inc. Complexity 21: 214–228, 2015

Robust H reliable control for uncertain switched neutral systems with distributed delays

This paper investigates the robust H∞ reliable control problem for a class of switched neutral systems with distributed delays that involve uncertainties and unknown disturbances. The uncertainties under consideration are norm-bounded, and disturbances are bounded in energy. A robust H∞ reliable state feedback controller is proposed to guarantee that the resulting closed-loop system is exponentially stable with a weighted H∞ disturbance attenuation level γ. The average dwell time approach is utilized for the H∞ performance analysis and controller design, and sufficient conditions are proposed in the form of linear matrix inequalities. Two numerical examples are given to illustrate the effectiveness of the result.

Dynamic characterization and modelling of a dual-axis beam steering device for performance understanding, optimization and control design

This paper presents a lumped thermal model of a dual-axis laser micromirror device for beam steering in a free-space optical (FSO) communication system, designed for fractionated spacecraft. An FSO communication system provides several advantages, such as larger bandwidth, smaller size and weight of the communication payload and less power consumption. A dual-axis mirror device is designed and realized using microelectromechanical systems technology. The fabrication is based on a double-sided, bulk micromachining process, where the mirror actuates thermally by joints consisting of v-grooves filled with the SU-8 polymer. The size of the device, consisting of a mirror, which is deflectable versus its frame in one direction, and through deflection of the frame in the other, is 15.4 × 10.4 × 0.3 mm3. In order to further characterize and understand the micromirror device, a Simulink state-space model of the actuator is set up using thermal and mechanical properties from a realized actuator. A deviation of less than 2% between the modelled and measured devices was obtained in an actuating temperature range of 20–200 °C. The model of the physical device was examined by evaluating its performance in vacuum, and by changing physical parameters, such as thickness and material composition. By this, design parameters were evaluated for performance gain and usability. For example, the crosstalk between the two actuators deflecting the mirror along its two axes in atmospheric pressure is projected to go down from 97% to 6% when changing the frame material from silicon to silicon dioxide. A feedback control system was also designed around the model in order to examine the possibility to make a robust control system for the physical device. In conclusion, the model of the actuator presented in this paper can be used for further understanding and development of the actuator system.

Modeling and Hydrodynamic Performance for a deep ocean manipulator based on Numerical Approach

An accurate dynamic model is important for both controller design and mission simulation, regardless of the control strategy employed. In this paper, a dynamic model for a 3500m underwater manipulator in flow disturbance is established based on Morison method. The technique provides a direct method for incorporating external environmental forces into the model. Applying the superposition principle, the hydraulic forces are decomposed into two parts, one is in static water condition and the other is in sea current condition. Through numerical calculation of hydrodynamics, the contribution of hydraulic resistance, buoyancy, sea steady flows and unsteady flows to manipulator’s dynamic are analyzed in sort. It offers a reliable basis for this 3-DOF manipulator controller design. The model derived is a closed form solution which can be utilized in modern model-based control schemes. The underwater test results verify the performance of controller in flow disturbance.

A Robust Variable Sampling Time BLDC Motor Control Design Based uponμ-Synthesis

The variable sampling rate system is encountered in many applications. When the speed information is derived from the position marks along the trajectory, one would have a speed dependent sampling rate system. The conventional fixed or multisampling rate system theory may not work in these cases because the system dynamics include the uncertainties which resulted from the variable sampling rate. This paper derived a convenient expression for the speed dependent sampling rate system. The varying sampling rate effect is then translated into multiplicative uncertainties to the system. The design then uses the popular μ-synthesis process to achieve a robust performance controller design. The implementation on a BLDC motor demonstrates the effectiveness of the design approach.

Hybrid Modeling of a DC-DC Series Resonant Converter: Direct Piecewise Affine Approach

A dc-dc resonant converter has the advantage of overcoming switching losses and electromagnetic interference which are the main limitations of high frequency power converters. Nevertheless, the modeling and stability analysis of dc-dc resonant converters are considerably more complex than pulsewidth modulation counterparts. The conventional averaged linearized model of the resonant converter has limitations due to averaging and linearization. First of all, the linearized model has large modeling error in presence of large variations of reference voltage and input voltage. Furthermore, Converging area for stabilizing controllers is smaller in the averaged model. In order to overcome these limitations, this paper presents a novel framework for modeling of dc-dc resonant converters. As dc-dc resonant converters are naturally switched systems with affine subsystems, a piecewise affine model is derived directly from the converter model. The new model is based on analysis of the resonant converter on state plane trajectories. It is also suitable for precise simulation and high performance controller design of resonant converters. In addition, a stability analysis theorem is provided for the proposed model. The simulation and experimental results on a dc-dc series resonant converter show the effectiveness of this modeling approach.

Modeling wave action effects in internal combustion engine air path systems: comparison of numerical and system dynamics approaches

The challenge of continuously improving engine fuel economy and emissions has pushed the automotive industry to adopt more efficient procedures for modeling, system simulation and model-based control. Such procedures require accurate and computationally efficient engine system simulation models that are able to predict the cylinder charge composition and the thermodynamic conditions. To this extent, reduced-order models for unsteady compressible flow systems, namely models derived from the fundamental conservation laws without over-simplifying the topology of the engine air path, are receiving considerable interest for performance simulation and control design. This paper presents a comparative study on modeling approaches for the prediction of one-dimensional unsteady compressible flow in the internal combustion engine air path system. Specifically, the paper compares a well-known second-order, shock-capturing finite-difference scheme with two novel solution methods, namely a finite-volume method and a model-order reduction method. The study aims at evaluating the ability of each method to trade-off the prediction accuracy and robustness with the computation time, in light of potential applications to real-time simulation. This is achieved by increasing the discretization length of each method, and evaluating the accuracy of the predicted response in the time and frequency domain. The characterization of the intake and exhaust flows in the manifolds of a single-cylinder engine is considered as a case study. The results are compared for the three solution methods at different discretization lengths to evaluate the ability of each model to retain accuracy and robustness. The computation times of the different methods are also evaluated. The results presented in this paper establish a clear trade-off between accuracy, stability and computation time for each solution method. This allows one to formulate considerations on the advantages and disadvantages of each method in light of potential applications to engine performance prediction, optimization and control design.

Active Fault Tolerant Control for Ultrasonic Piezoelectric Motor

Active Fault Tolerant Control for Ultrasonic Piezoelectric MotorUltrasonic piezoelectric motor technology is an important system component in integrated mechatronics devices working on extreme operating conditions. Due to these constraints, robustness and performance of the control interfaces should be taken into account in the motor design. In this paper, we apply a new architecture for a fault tolerant control using Youla parameterization for an ultrasonic piezoelectric motor. The distinguished feature of proposed controller architecture is that it shows structurally how the controller design for performance and robustness may be done separately which has the potential to overcome the conflict between performance and robustness in the traditional feedback framework. A fault tolerant control architecture includes two parts: one part for performance and the other part for robustness. The controller design works in such a way that the feedback control system will be solely controlled by the proportional plus double-integralPI2 performance controller for a nominal model without disturbances andH∞robustification controller will only be activated in the presence of the uncertainties or an external disturbances. The simulation results demonstrate the effectiveness of the proposed fault tolerant control architecture.

Fuzzy Control Strategy Applied to Adjustment of Front Steering Angle of a 4WSD Agricultural Mobile Robot

This paper presents the preliminary studies of the control strategy based in fuzzy logic, projected for the steering system of AGRIBOT project that consist of a wheeled autonomous mobile robotic in real scale endowed with four independent steering and driven wheels (4WSD). In this work we present a preliminary fuzzy controller design applied to front steering angle, using a multivariable plant which incorporates simplified linear model of lateral dynamics of a vehicle whose input are linear combination of rear and front steering angles. The fuzzy control strategy was decided because provides flexible way to deploy with embedded systems. Simulations are used to illustrate the designed controller performance. We use Ackerman geometry to trace front steering angle that allows the vehicle to perform correctly a given maneuver preserving a minimum level of stability and maneuverability. The goal is to establish a relationship between steering input commands and the control commands to the actuators so that it is possible to adjust the attitude of the actuators over the movement axis, as the trajectory change.

Generalized Predictive Control for Gas Supply System in a Proton Exchange Membrane Fuel Cell

Gas supply system in a proton exchange membrane fuel cell power system consists of hydrogen supply and oxygen supply. In order to improve the system output performance and maintain the pressure difference between the anode and cathode at the setting points under the variational load currents, a generalized predictive control strategy is applied to the gas supply system of a proton exchange membrane fuel cell in this paper. The fuel cell stack and gas supply system were modeled for the purpose of performance analysis and controller design. And then the designed generalized predictive controller was implemented to control the hydrogen flow rate and oxygen compressor voltage. The simulation results illustrated that the proposed controller can provide better response characteristics of the pressure difference, hydrogen and oxygen supply system as compared with PID controller.

상태공간 모델링에 의한 공작기계용 수냉각기의 최적제어기 설계

ABSTRACT:Typical temperature control methods of a cooler for machine tools are hot-gas bypass and compressor variable speed control. The hot-gas bypass system has been widely used to control the cooler temperature in many general industrial fields. On the contrary, the compressor variable speed control is focused on special fields such as aerospace and high precision machine tools which need high precision control. The variable speed control system usually has two control variables such as target temperature and superheat. In other words, the variable speed control sys-tem is basically multi-input multi-output(MIMO) system. In spite of MIMO system, the proportional integral derivative(PID) feedback control methodology that based on single-input single-output (SISO) system is generally used for designing the variable speed control system. Therefore, it is inevitable to describe transfer functions for dynamic behaviors of every controlled variables and decide the PID gains with tremendous iteration process. Moreover, the designed PID gains do not provide optimum system performances. To solve these problems, high performance controller design method based on a state space model is suggested in this paper. An optimum controller is designed to minimize both control errors and energy inputs. This method was more simple to describe dynamic behaviors and easier to design the cooler controller which is MIMO system.Keywords:Water cooler(수냉각기), Optimum control(최적제어), State space model(상태공간 모델), Compressor variable speed control(압축기 가변속 제어), Multi-input multi- output system(다입력 다출력 시스템), State variable(상태변수)