4,355 research outputs found
Universal direct tuner for loop control in industry
This paper introduces a direct universal (automatic) tuner for basic loop control in industrial applications. The direct feature refers to the fact that a first-hand model, such as a step response first-order plus dead time approximation, is not required. Instead, a point in the frequency domain and the corresponding slope of the loop frequency response is identified by single test suitable for industrial applications. The proposed method has been shown to overcome pitfalls found in other (automatic) tuning methods and has been validated in a wide range of common and exotic processes in simulation and experimental conditions. The method is very robust to noise, an important feature for real life industrial applications. Comparison is performed with other well-known methods, such as approximate M-constrained integral gain optimization (AMIGO) and Skogestad internal model controller (SIMC), which are indirect methods, i.e., they are based on a first-hand approximation of step response data. The results indicate great similarity between the results, whereas the direct method has the advantage of skipping this intermediate step of identification. The control structure is the most commonly used in industry, i.e., proportional-integral-derivative (PID) type. As the derivative action is often not used in industry due to its difficult choice, in the proposed method, we use a direct relation between the integral and derivative gains. This enables the user to have in the tuning structure the advantages of the derivative action, therefore much improving the potential of good performance in real life control applications
First order plus frequency dependent delay modeling : new perspective or mathematical curiosity?
The first-order-plus-dead-time model (FOPDT) is a popular simplified representation of higher order dynamics. However, a well known drawback is the rapid decrease of the frequency response accuracy with increasing process order. This especially applies to the higher frequency range. Literature offers solutions by extending this three parameter model with more parameters. Here, a fractional dead time is proposed. As such, a Frequency-Dependent Delay (FDD) is introduced, which offers a better approximation. As the fractional-order term introduces nonlinear coupling between the phase and the magnitude of the process, the fitting of the function becomes an iterative process, so a constrained multi-objective optimization is needed. This novel model, first-order-plus-frequency-dependent-delay or FOPFDD is fitted on a real electrical ladder network of resistors and capacitors of four and eight parts. The classic model, which is clearly a special case of the new model, is outperformed in the entire bandwidth
A single-step identification strategy for the coupled TITO process using fractional calculus
The reliable performance of a complete control system depends on accurate model information being used to represent each subsystem. The identification
and modelling of multivariable systems are complex and challenging due to cross-coupling. Such a system may require multiple steps and decentralized
testing to obtain full system models effectively. In this paper, a direct identification strategy is proposed for the coupled two-input two-output
(TITO) system with measurable input–output signals. A well-known closed-loop relay test is utilized to generate a set of inputs–outputs data from a single
run. Based on the collected data, four individual fractional-order transfer functions, two for main paths and two for cross-paths, are estimated from
single-run test signals. The orthogonal series-based algebraic approach is adopted, namely the Haar wavelet operational matrix, to handle the fractional
derivatives of the signal in a simple manner. A single-step strategy yields faster identification with accurate estimation. The simulation and experimental
studies depict the efficiency and applicability of the proposed identification technique. The demonstrated results on the twin rotor multiple-input multiple-
output (MIMO) system (TRMS) clearly reveal that the presented idea works well with the highly coupled system even in the presence of measurement
noise
Identification scheme for fractional Hammerstein Models with the delayed Haar Wavelet
The parameter identification of a nonlinear Hammerstein-type process is likely to be complex and challenging due
to the existence of significant nonlinearity at the input side. In this paper, a new parameter identification strategy for a block-oriented Hammerstein process is proposed using the Haar wavelet operational matrix (HWOM). To determine all the parameters in the Hammerstein model, a special input excitation is utilized to separate the identification problem of the linear subsystem from the complete nonlinear process. During the first test period, a simple step response data is utilized to estimate the linear subsystem dynamics. Then, the overall system response to sinusoidal input is used to estimate nonlinearity in the process. A single-pole fractional order transfer function with time delay is used to model the linear subsystem. In order to reduce the mathematical complexity resulting from the fractional derivatives of signals, a HWOM based algebraic approach is developed. The proposed method is proven to be simple and robust in the presence of measurement noises. The numerical study illustrates the efficiency of the proposed modeling technique through four different nonlinear processes and results are compared with existing methods
Robust controller design: Recent emerging concepts for control of mechatronic systems
The recent industrial revolution puts competitive requirements on most manufacturing and mechatronic
processes. Some of these are economic driven, but most of them have an intrinsic projection on
the loop performance achieved in most of closed loops across the various process layers. It turns out
that successful operation in a globalization context can only be ensured by robust tuning of controller
parameter as an effective way to deal with continuously changing end-user specs and raw product properties.
Still, ease of communication in non-specialised process engineering vocabulary must be ensured
at all times and ease of implementation on already existing platforms is preferred. Specifications as
settling time, overshoot and robustness have a direct meaning in terms of process output and remain
most popular amongst process engineers. An intuitive tuning procedure for robustness is based on linear
system tools such as frequency response and bandlimited specifications thereof. Loop shaping remains a
mature and easy to use methodology, although its tools such as Hinf remain in the shadow of classical
PID control for industrial applications. Recently, next to these popular loop shaping methods, new tools
have emerged, i.e. fractional order controller tuning rules. The key feature of the latter group is an
intrinsic robustness to variations in the gain, time delay and time constant values, hence ideally suited
for loop shaping purpose. In this paper, both methods are sketched and discussed in terms of their
advantages and disadvantages. A real life control application used in mechatronic applications illustrates the proposed claims. The results support the claim that fractional order controllers outperform in terms
of versatility the Hinf control, without losing the generality of conclusions. The paper pleads towards
the use of the emerging tools as they are now ready for broader use, while providing the reader with a
good perspective of their potential
Fractional - order system modeling and its applications
In order to control or operate any system in a closed-loop, it is important to know its behavior in the form of
mathematical models. In the last two decades, a fractional-order model has received more attention in system identification instead of classical integer-order model transfer function. Literature shows recently that some techniques on fractional calculus and fractional-order models have been presenting valuable contributions to real-world processes and achieved better results. Such new developments have impelled research into extensions of the classical identification techniques to advanced fields of science and engineering. This article surveys the recent methods in the field and other related challenges to implement the fractional-order derivatives and miss-matching with conventional science. The comprehensive discussion on available literature would help the readers to grasp the concept of fractional-order modeling and can facilitate future investigations. One can anticipate manifesting recent advances in fractional-order modeling in this paper and unlocking more opportunities for research
Tuning fractional PID controllers for a Steward platform based on frequency domain and artificial intelligence methods
In this paper, two methods to tune a fractional-order PI (lambda) D (mu) controller for a mechatronic system are presented. The first method is based on a genetic algorithm to obtain the parameter values for the fractionalorder PI (lambda) D (mu) controller by global optimization. The second method used to design the fractional-order PI (lambda) D (mu) controller relies on an auto-tuning approach by meeting some specifications in the frequency domain. The real-time experiments are conducted using a Steward platform which consists of a table tilted by six servo-motors with a ball on the top of the table. The considered system is a 6 degrees of freedom (d.o.f.) motion platform. The feedback on the position of the ball is obtained from images acquired by a visual sensor mounted above the platform. The fractional-order controllers were implemented and the performances of the steward platform are analyzed
- …