Two-input Two-output Research Articles

Fast prototyping method for the active vibration damping system of mechanical structures

A fast prototyping method for the active vibration control system of 3D mechanical structures is presented in the paper. To control such system piezo-stack actuators were used. The subsequent steps of the prototyping procedure are explained for the bar structure as an example. The Finite Element Modeling (FEM) approach was used to find the quasi-optimal location of piezo-stacks in the structure. Next, the structure with inbuilt piezo-actuators was designed and tested in the laboratory. The more accurate mathematical model of the structure dynamics was obtained as a result of the identification procedure.The mathematical model was reduced and decoupled to change the Two Input Two Output (TITO) system into two Single Input Single Output (SISO) systems. Such approach allowed us to design simple control laws with the aid of the computer simulation procedure. In the last chapter the tests on the laboratory stand of the active vibration control system with local Proportional-Derivative (PD) controllers are described. Experimental results have proved that these PD controllers work good increasing the damping level. Additional damping causes an excellent vibration reduction of the whole mechanical structure.

Signal Filtering in PID Control

The major input signals entering the PID controller are; the set point, the process output, and measurable load disturbances. By feeding these signals through suitable filters, the properties of the feedback loop can be improved significantly. This presentation will treat set point handling, feedforward from load disturbances, TITO (two input two output) control, noise filtering, and process dynamics compensation. An industrial case from the steel industry is also discussed.

Stabilization of TITO Systems over Parallel SNR-Constrained AWN channels

This paper concerns the stabilization of two-input two-output (TITO) discrete-time linear time-invariant (LTI) systems over parallel additive white noise (AWN) channels, in which each individual channel is independently constrained in SNR. Necessary and sufficient conditions for stabilizability are obtained on the SNR's of the channels, in terms of the unstable poles and non minimum phase zeros of the plant, for both state and output feedback control.

The design and development of multivariable controls with the application for energy management of hybrid electric vehicles

In this paper, we overview the importance and design of robust feedback control in challenging application of Hybrid Electric Vehicle (HEV) energy management. The HEV dynamic is highly-coupled two-input two-output with severe interactions between internal combustion engine and electric motor. Moreover, it is subjected to parametric uncertainties (engine lag, rotational moment of inertia and damping), unmodeled dynamic (ignition/combustion delay) and unmeasurable exogenous disturbances (engine torque loss and clutch torque). We demonstrate that a robust multivariable design has great potential to provide guaranteed stability- and performance-robustness for this challenging application. Simulation results also verify the above leading towards reduced calibration cost and time.

Modeling and Control of a Complex Interacting Process

In this paper, two efficient control algorithms are discussed viz., Linear Quadratic Regulator (LQR) and Dynamic Matrix Controller (DMC) and their applicability has been demonstrated through case study with a complex interacting process viz., a laboratory based four tank liquid storage system. The process has Two Input Two Output (TITO) structure and is available for experimental study. A mathematical model of the process has been developed using first principles. Model parameters have been estimated through the experimentation results. The performance of the controllers (LQR and DMC) has been compared to that of industrially more accepted PID controller.

Digital Control of a Waste Water Treatment Plant

The Activated Sludge Process (ASP) is arguably the most popular bioprocess utilized in the treatment of polluted water. The ASP is described by means of a nonlinear model and results on a Two-Input Two-Output multivariable system. In this paper a discrete time digital control is proposed where the design of a decentralized controller is faced. Local controllers are given the form of a Two-Degree-of-Freedom PI controller tuned using the data-driven Virtual-Reference Feedback tuning approach.

Analysis and design of partly networked architectures for two-input two-output LTI systems

AbstractThis article deals with the control of a two-input two-output (TITO) discrete time LTI plant, where one control signal is to be sent through a transparent channel, and the remaining control signal has to be sent through a channel that presents signal-to-noise ratio (SNR) constraints. For this situation, we study three different control architectures: state feedback, output feedback, and output feedback enriched with feedback around the constrained channel. We explore how the stability, and the best achievable performance, depend on the location of the SNR constrained channel for each architecture. An interesting conclusion of this work is that the best channel choice, when stability is the only concern, may be inadequate when the focus is on performance. A numerical example is included to illustrate our results.

The Asymmetric Golden Code for Fast Decoding on Time-Varying Channels

The golden code is a full-rate full-diversity space---time code for the two-input two-output channel with good performance but high decoding complexity. The overlaid Alamouti codes were recently proposed as an alternative; in exchange for a slight performance penalty, they have lower decoding complexity on quasistatic channels with QAM alphabets. However, the complexity advantage of the overlaid codes vanishes for time-varying channels. This paper proposes the asymmetric golden code, a novel full-rate and full-diversity space---time code for the two-input two-output channel that offers reduced-complexity decoding on both quasistatic and time-varying channels.

Tuning fuzzy PD and PI controllers using reinforcement learning

In this paper, we propose a new auto-tuning fuzzy PD and PI controllers using reinforcement Q -learning (QL) algorithm for SISO (single-input single-output) and TITO (two-input two-output) systems. We first, investigate the design parameters and settings of a typical class of Fuzzy PD (FPD) and Fuzzy PI (FPI) controllers: zero-order Takagi–Sugeno controllers with equidistant triangular membership functions for inputs, equidistant singleton membership functions for output, Larsen’s implication method, and average sum defuzzification method. Secondly, the analytical structures of these typical fuzzy PD and PI controllers are compared to their classical counterpart PD and PI controllers. Finally, the effectiveness of the proposed method is proven through simulation examples.

PID controller design of TITO system based on ideal decoupler

The proposed method for designing multivariable controller is based on ideal decoupler D( s) and PID controller optimization under constraints on the robustness and sensitivity to measurement noise. The high closed-loop system performance and robustness are obtained using the same controller in all loops. The method is effective despite the values and positions of the right half plane zeros and dead-times in the process transfer function matrix G p( s). The validity of the proposed multivariable control system design and tuning method is confirmed using a test batch consisting of Two-Input Two-Output (TITO) stable, integrating and unstable processes, and one Three-Input Three-Output (TITO) stable process.

Improved Coupled Tank Liquid Levels System Based on Swarm Adaptive Tuning of Hybrid Proportional-Integral Neural Network Controller

Problem statement: Accuracy and stability of many systems in chemical and process industries which has Two-Input Two-Output (TITO) is one of the key factors of process which have cross coupling between process input and output. Approach: Unlike traditional neural network weight adaptation using gradient descent method, Particles Swarm Optimization (PSO) technique was utilized for adaptive tuning of neural network weights adjustment and fine tuning the controller’s parameters. Design approach for controlling liquid levels of Coupled Tank TITO system by using hybrid PI-Neural Network (hybrid PI-NN) controllers. Results: Tuning method for parameters of improved hybrid PI-NN controller was also discussed. Conclusion: Performances of proposed method also compared with PID-NN controllers, it was shown that hybrid PI-NN controller exhibited better performance in terms of transient response analysis.

Adaptive Control of Three – Tank – System Using Polynomial Methods

Abstract Adaptive control of a three – tank - system laboratory model is presented. The objective laboratory model is a two input – two output (TITO) nonlinear system. It is based on experience with authentic industrial control applications. Two control algorithms utilizing polynomial theory and pole – placement were applied and compared. The first one is based on the traditional 1DOF (one – degree of freedom) configuration of the closed loop, the second one applies a decoupling method to suppress undesired cross – coupling. The algorithms implemented as self – tuning controllers are then used for control of the model. Results of real-time experiments are also included. Quality of control achieved by both methods is compared and discussed.

Delay‐compensated controllers for two‐input/two‐output (TITO) multivariable processes

AbstractA decentralized controller design based on the direct synthesis method for two‐input/two‐output (TITO) processes in the Smith predictor configuration is proposed. The decentralized controllers are designed individually on the basis of the diagonal individual transfer functions of the process. Using the direct synthesis principle, the two decentralized controllers are designed using the individual diagonal transfer functions of the process matrix and the individual desired diagonal closed‐loop transfer functions. Further, these direct synthesis controllers are implemented in the Smith predictor configuration for each output. While converting from the synthesis controller to the Smith predictor configuration, the decentralized controller parameters are directly obtained in terms of the individual closed‐loop desired tuning parameters. The method is compared with the recently reported methods. Copyright © 2007 Curtin University of Technology and John Wiley & Sons, Ltd.

ENVIRONMENT FOR CAD AND VERIFICATION OF SELF – TUNING CONTROLLERS

The contribution deals with an adaptive controllers’ library designed under MATLAB – Simulink environment. The library enables design and verification of two input – two output (TITO) discrete self – tuning controllers. It is a completely open system based on Simulink features. Design of the TITO controllers that are included into the library is based on polynomial methods. The controllers are based on various configurations of the closed loop system. Several decoupling compensators are also applied. The main idea of self – tuning controllers is discussed. In the paper are presented also several examples. The possibility of developing real – time applications using MATLAB Real – Time Workshop is discussed.

Theoretical and experimental study on PMD-supported transmission using polarization diversity in coherent optical OFDM systems

In this paper, we conduct theoretical and experimental study on the PMD-supported transmission with coherent optical orthogonal frequency-division multiplexing (CO-OFDM). We first present the model for the optical fiber communication channel in the presence of the polarization effects. It shows that the optical fiber channel model can be treated as a special kind of multiple-input multiple-output (MIMO) model, namely, a two-input two-output (TITO) model which is intrinsically represented by a two-element Jones vector familiar to the optical communications community. The detailed discussions on various coherent optical MIMO-OFDM (CO-MIMO-OFDM) models are presented. Furthermore, we show the first experiment of polarization-diversity detection in CO-OFDM systems. In particular, a CO-OFDM signal at 10.7 Gb/s is successfully recovered after 900 ps differential-group-delay (DGD) and 1000-km transmission through SSMF fiber without optical dispersion compensation. The transmission experiment with higher-order PMD further confirms the immunity of the CO-OFDM signal to PMD in the transmission fiber. The nonlinearity performance of PMD-supported transmission is also reported. For the first time, nonlinear phase noise mitigation based on receiver digital signal processing is experimentally demonstrated for CO-OFDM transmission.

Analytical Design of Decoupling Internal Model Control (IMC) Scheme for Two-Input−Two-Output (TITO) Processes with Time Delays

In this paper, a new decoupling control scheme, in terms of an internal model control (IMC) structure, is proposed for two-input−two-output (TITO) processes with time delays. Noteworthy improvement of the decoupling regulation can be achieved for the nominal system output responses, and moreover, either of the system output responses can be quantitatively regulated by virtue of the analytical relationship between the adjustable parameters of the decoupling controller matrix and the nominal system transfer matrix. The ideally optimal controller matrix is analytically derived by proposing the practically desired diagonal system transfer matrix, in terms of the robust H2 optimal performance objective. Because of the difficulty of physical implementation, its practical form is carefully configured according to whether there exist any complex right-half-plane (RHP) zeros in the process transfer matrix determinant. At the same time, tuning constraints for the proposed decoupling controller matrix to hold the co...

BLIND SYSTEM IDENTIFICATION USING MATRIX MEAN DIFFERENTIAL CEPSTRUM WITH QR-CHOLESKY DECOMPOSITION

A further development of the matrix mean differential cepstrum technique for blind identification of convolved mixtures in multiple-input-multiple-output mechanical systems is presented. The stability of the technique for application on the whitened response measurements can be improved with the use of the QR-Cholesky decomposition instead of the SVD-EVD set. Two simulated two-input two-output, two degree of freedom systems of differing damping coefficients are tested. The improved results with smoother frequency response functions of the system are presented and compared to prior results.

MULTI AGENT INTELLIGENT CONTROL OF CENTRALIZED HVAC SYSTEMS

The perspective of Multi Agent Systems (MAS) implementation in thermal control of centralized HVAC systems is considered. MAS are implemented in all functional levels of hierarchical HVAC control system: estimation of representative control variables by agent based softsensing, evaluation of Predicted Mean Vote (PMV) index using intelligent agents, local control applying agent-based Ant Colony Optimization (ACO). A non-square control problem of realization comfort is solved via ACO. Software agents are realized into the framework of JADE – plathform in JAVA. Simulation results are presented for single input-two output (SITO) control system.

Modelling the Control of an Isolated Power System Based on Diesel and Pitch Controlled Wind Generation

This paper deals with the control of a stand alone power system comprised of a pitch controlled wind turbine and two diesel units. First, a single-input single-output (SISO) self-tuning regulator (STR) is designed for blade-pitch control, with a conventional diesel governor control. Then, a two-input two-output (TITO) STR is used for coordinated pitch and diesel governor controls. Finally a case study is made with a superconducting magnetic energy storage unit (SMES), introduced as a damping device. In this case, a three-input three-output STR controls the wind-diesel-SMES system in a co-ordinated manner. The design of the various control schemes ensures that the system performs well under both wind and load disturbances.

Robust decentralized parameter identification for two-input two-output process from closed-loop step responses

In this paper, a novel parameter identification method for closed-loop two-input two-output (TITO) processes from step-test is proposed. Through sequential step change of set points, the coupled closed-loop TITO system is decoupled equivalently into four independent single open-loop processes with same input signal acting on the four transfer functions. Consequently, existing identification methods for single-loop process can be extended to TITO systems and the parameters of first- or second-order plus dead-time models for each transfer function can be directly obtained by using the linear regression equations derived for the decoupled identification system. The proposed method is simple for engineering application and robust in the presence of large amounts of measurement noise. Simulation examples are given to show both effectiveness and practicality of the identification method for a wide range of multivariable processes.