Single PID Controller Research Articles

Real‐Time Control and Identification of a Thermal Process Based on Multiple‐Modeling Approach

AbstractThis article presents implementation of Real‐Time Control and Identification algorithms based on a Multiple‐Modeling approach for an experimental thermal process. The thermal process is a nonlinear plant; therefore, based on variations of the input and disturbance, four local operating regimes are defined. The linear local ARMAX models are identified for different regimes and integrated into a NARMAX model by combining them via proper validity and interpolation functions. Results of modeling the plant with a single model and multiple models show superior performance of the Multiple‐Modeling technique which is also more flexible. Moreover, the Real‐Time Control of the plant with four locally designed controllers is addressed. The platform used for the Real‐Time implementation is Matlab/Simulink/Real‐Time‐Workshop with Visual C++ and Watcom compilers using a DAQ interface. The Real‐Time application of the global controller based on the Multiple‐Model approach demonstrates excellent performance for this design when compared to a single PID controller.

Controller Design for Integrating Processes in SISO or MIMO Systems

A two-step design to control integrator processes in an SISO or MIMO system is proposed. For an SISO system, the first step of the design is to stabilize the integrator process with P&D modes in a secondary loop to achieve good stability robustness and modest performance. In the second step of design, a P&I controller in the primary loop is derived to improve the overall performance. By this way, an equivalent two-element control system comprising of a single PID control loop and a pre-filter applying on the set-point command is derived. The same design approach is then applied to design multiloop SISO controllers for MIMO processes, where integrating behavior exists. By employing the same two-step design and the direct method of Huang et al. (2003), 2-df multi-loop PI/PID controllers can be obtained. The Simulation results show that this presented method is effective for both SISO and MIMO process with integrators.

잉크젯 프린터 용지 이송 장치의 정밀 위치 제어를 위한 이중 PID 제어기의 설계

The ink jet printer media advance system is required to be exactly driven to the target position via tracking the reference velocity profile to obtain the high quality print image. A single gain PID controller is not sufficient to fulfill the control objectives, the exact velocity tracking and the accurate positioning, at the same time. A dual PID controller and its switching strategy are presented in this paper to achieve the control objectives. The media advance system is controlled by two separate PID controllers, one of which is for velocity control, and the other is for position control. A PID controller controls the velocity of the media advance system until it reaches the predetermined switching position. When the media advance system passes the predetermined position, the controller is switched to the other PID controller which is more profitable for exact positioning. The switching position is determined by the estimated stop distance. The simulation and experimental results are presented to show the validity and effectiveness of the proposed controller.

Fieldbus: more than a communication link

A virtual instrument alone is nonsensical. Measuring a voltage or a current with a multi-meter is much simpler, faster, and cheaper than using a virtual measurement environment. A dedicated instrument can perform more accurate and reliable measures than any virtual instrument. On the other hand, if a measurement is a combination of different data, if it has to be mathematically manipulated, or transmitted, or recorded, or displayed...for these situations, virtual instruments prove their worth. The concept can extend to virtual controllers. A hardware controller can easily implement a single PID control loop, but virtual devices are much more flexible in implementing multiple control strategies. Virtual devices give the best results when solving complex measurement and control tasks. Let's define the meaning of the two words that comprise virtual system. A system has specific characteristics: 1) integration of multiple actuators and sensors; 2) flexibility in defining the measurement or control target; 3) integration of different subsystems; 4) capacity of performing multiple tasks; and 5) interface with other systems. To summarize, when we speak of a virtual instrument, what we actually mean is "an instrument based on digital technology" that is a hardware platform, an operating system, and a development environment. In a sense, it may be preferable to speak of "intelligent systems" rather than of virtual systems. In the I&M world, the terms "intelligent" and "virtual" can roughly be considered synonyms. An instrument is intelligent if its human designer is intelligent. Innovation rests with the capacity of transforming physical principles into reliable field devices. The virtual instrument defined in the fieldbus profile is a representation that is necessary for interfacing the instrument with the data acquisition or control system, but it has nothing to do with the instrument itself. Through fieldbus it is possible to create a really distributed virtual measurement system. The instrument interface is virtual (digital and programmable), but the instrument itself is all but virtual.

Control of Chemical Reactors Using Multiple-Model Adaptive Control (MMAC)

Multiple-Model Adaptive Control (MMAC) is shown to be an effective strategy for controlling nonlinear chemical processes. In this paper, MMAC is applied to two difficult control problems that may be encountered in continuous stirred tank reactors (CSTRs). In the first example, product concentration is controlled in an isothermal CSTR exhibiting input multiplicities and nonminimum phase behavior (Van de Vusse reaction). The MMAC configuration provides disturbance rejection where a fixed-parameter PID controller fails. The second example involves temperature control of a CSTR which has output multiplicities. While a single PID controller can stabilize the plant over a large operating range, its performance can be quite poor since the plant dynamics vary widely. MMAC is shown to give significantly better performance when moving from the open-loop stable regions to the open-loop unstable operating region.