Virtual Reference Feedback Tuning Research Articles

Application of multivariate virtual reference feedback tuning for wastewater treatment plant control

The objective of this paper is to apply the Virtual Reference Feedback Tuning (VRFT) to Multiple-Input Multiple-Output (MIMO) control strategies in wastewater treatment plants (WWTPs). Using the Benchmark Simulation Model No. 1 (BSM1) as a case study, the proposed data-driven approach provides reduced-order controllers only using a batch of input–output data points (i.e. manipulated variable—controlled variable), obtained from an open-loop experiment. The methodology also includes a pre-processing step that subtracts the impact of influent variability and sensor noise from the output signals. The possible interactions amongst different control loops are handled using a decoupling approach where each control signal is computed depending on the error signal of all the loops at the same time. In order to test the methodology, several control strategies are evaluated via simulation. The results show that substantial improvements in the plant performance can be obtained when controllers are implemented.

Design of an Implicit GMV-PID Controller Using Closed Loop Data

SUMMARY In industrial processes, PID control has been applied in many real systems. The control performance strongly depends on the PID parameters. Although some schemes for tuning PID parameters have been proposed, these schemes need system parameters which are estimated by system identification in order to calculate the PID parameters. On the other hand, model-free controller design schemes represented by virtual reference feedback tuning (VRFT) or FRIT have received much attention in the last few years. These methods can calculate control parameters using closed loop data and are expected to reduce computational costs. In this paper, a type of implicit PID controller using closed loop data is proposed. In the proposed method, the PID parameters are calculated on the basis of the implicit generalized minimum variance control. The control performance can be suitably adjusted by means of only a user-specified parameter. The effectiveness of the proposed method is numerically and experimentally evaluated.

Data-driven robust PID tuning toolbox

In this paper, a toolbox is presented for the parameter tuning of PID controllers based on the Virtual Reference Feedback Tuning. The VRFT is a data-driven methodology that uses only data to find the parameters of the controller. In order to add robustness to the design, a test is proposed and implemented in the tool that use an approximation of the multiplicative uncertainty in an “Internal Model Control” like framework to check if the controller found is robustly stable.

Non-iterative direct data-driven controller tuning for multivariable systems: theory and application

In this study, a data-driven technique is proposed to deal with multivariable fixed-order controller design. The method is based on the virtual reference feedback tuning (VRFT) philosophy and thus does not require any model of the plant. Unlike standard VRFT for SISO systems, extended instrumental variables and variance weighting are used to counteract the effect of noise and achieve consistent controller estimate with a single set of input-output data. The proposed strategy is numerically compared to other existing direct and indirect techniques on a benchmark simulation example. The effectiveness of the method is finally tested on the airpath control of a real diesel engine.

Multivariable PI control for a boiler plant benchmark using the Virtual Reference Feedback Tuning

In this work, the Virtual Reference Feedback Tuning is applied to the control of a boiler plant benchmark. Only data (without any modelling step) was used to compute a series of PI controllers for both a decentralized and a complete multi-loop control strategies. When compared with other PI controllers, it was found that a better tuning of the controller was achieved yielding better closed-loop results. The original VRFT method was enhanced with a series of constraints during the optimization process that allows the user to select the position of the zero of the controller.

Direct data‐driven control of linear time‐delay systems

AbstractThis paper presents an extension of the Virtual Reference Feedback Tuning (VRFT) methodology dedicated to linear time‐delay systems with known delay and unknown dynamics. The standard VRFT is not well suited for systems with dominant time‐delay as it yields high order controllers. The proposed direct approach, relying on a Smith Predictor structure, guarantees the same level of performance as the standard VRFT but with lower order controllers. The joint direct data‐driven design of the controller and the predictor is facilitated by the introduction of an ad‐hoc optimization initialization. Effectiveness and robustness to uncertainty in the time‐delay estimation are shown in a vehicle dynamics control problem.Copyright © 2011 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society

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.

Virtual Reference Feedback Tuning for non-minimum phase plants

Model reference control design methods fail when the plant has one or more non-minimum phase zeros that are not included in the reference model, leading possibly to an unstable closed loop. This is a very serious problem for data-based control design methods, where the plant is typically unknown. In this paper, we extend the Virtual Reference Feedback Tuning method to non-minimum phase plants. This extension is based on the idea proposed in Lecchini and Gevers (2002) for Iterative Feedback Tuning. We present a simple two-step procedure that can cope with the situation where the unknown plant may or may not have non-minimum phase zeros.

Asymptotic statistical analysis for model-based control design strategies

In this paper, we generalize existing fundamental limitations on the accuracy of the estimation of dynamic models. In addition, we study the large sample statistical behavior of different estimation-based controller design strategies. In particular, fundamental limitations on the closed-loop performance using a controller obtained by Virtual Reference Feedback Tuning (VRFT) are studied. We also extend our results to more general estimation-based control design strategies. We present numerical examples to show the application of our results.

Virtual Reference Feedback Tuning for linear parameter-varying systems

AbstractIn this work, a data-driven algorithm is proposed to directly design a gain-scheduled model-reference controller without need of identifying and transforming a model of the process. The method is based on the Virtual Reference Feedback Tuning (VRFT) approach and it guarantees good performance if model-matching can be achieved. A preliminary study of the undermodeling case is proposed to lay the groundwork of future research.

Three degrees of freedom Virtual Reference Feedback Tuning design and its application to wastewater treatment plant control

AbstractIn this paper, a three degrees of freedom (two degrees of freedom plus disturbance feedforward action) controller, tuned with the Virtual Reference Feedback Tuning is presented and applied to a wastewater treatment plant. The chosen framework is the one established in the Benchmark Simulation Model 1. Two loops were applied: control of nitrate concentration at the last anoxic section of the plant by manipulating the internal recycle flow rate using a two-degrees of freedom PI and a cascade plus feedforward approach to control ammonia at the last aeration section by manipulating the setpoint of the dissolved oxygen controller at the last aeration section using ammonia measurements from the influent. The results are very close to other more advanced approaches applied to the plant in the same conditions, therefore showing the usability of model-free approach for wastewater treatment plant control.

Internal Model Controller tuning using the Virtual Reference Approach with Robust Stability

AbstractIn this paper a data-driven methodology based on the Virtual Reference Feedback Tuning is presented for the tuning of Internal Model Controllers. A data based test is presented to check the robust stability of the controller in the loop, taking advantage of the control structure. Two different examples are shown where the presented method successfully controls a non-minimum phase discrete time plant and a non-linear continuous time process.

Fast tuning of cascade control systems

AbstractIn this paper, an algorithm for direct data-driven design of cascade control system is proposed and analysed. The procedure is based on the Virtual Reference Feedback Tuning (VRFT) approach but it allows to tune either the inner and the outer loops by means of a single set of experimental data. The main differences between the standard VRFT and the proposed approach are highlighted and analyzed. The design technique is finally applied on a micro-positioning control problem for Electro-HydroStatic Actuators (EHSAs).

Data-driven Nonlinear Control of a Solid Oxide Fuel Cell System

AbstractSolid oxide fuel cells (SOFCs) are considered to be one of the most important clean, distributed resources. However, they present a challenging control problem owing to the SOFC's slow dynamics, nonlinearity and tight operating constraints. In this paper, we propose a novel data-driven nonlinear control strategy to solve the SOFC control problem by combining a virtual reference feedback tuning (VRFT) method with support vector machine (SVM). In order to fulfill the requirement for fuel utilization and control constraints, a dynamic constraints unit plus an anti-windup scheme are adopted. In addition, a feedforward loop is designed to deal with the current disturbance. Detailed simulations are given to demonstrate the feasibility of control application to fuel cell plants.

Model-free control for active braking systems in sport motorcycles

Designing effective braking controllers for sport motorcycles is a very challenging task, due to the complex vehicle dynamics and the highly nonlinear nature of the road-tire interactions. These facts make it difficult to devise control-oriented dynamical models capable of describing the dynamics of interest in all working conditions. Thus, this paper proposes a model-free approach to solve the problem. Specifically, a linear controller designed via the virtual reference feedback tuning (VRFT) approach is complemented with a data-driven nonlinear compensator to yield an effective braking controller within the Mixed Slip-Deceleration (MSD) framework. The proposed approach relies on an ad-hoc adaptation of the VRFT controller design which takes into account the presence of the dynamic compensation. The effectiveness of the proposed design approach is assessed on a multibody simulator.

Virtual Reference Feedback Tuning (VRFT) design of cascade control systems with application to an electro-hydrostatic actuator

In this work an algorithm for direct design of cascade control system is presented. The algorithm is based on the Virtual Reference Feedback Tuning (VRFT) paradigm and allows tuning both the internal loop controller and the external loop control in a single shot based on an I/O data set collected in a single experiment on the plant. Application of this control tuning procedure will be performed on an Electro-HydroStatic Actuator (EHSA) prototype, a new generation of hydraulic actuator providing the main advantages of both mechanical and hydraulic actuators but reducing most of the drawbacks. Experimental validation is presented showing that the designed control system provides good control accuracy and robustness.

Closed Loop Identification Based on the Virtual Reference Feedback Tuning Applied to a Virtual Two-Degree-of-Freedom Control System

A new identification method with respect to the parameter tuning of a controller is presented. Here, we introduce a virtual two-degree-of-freedom control structure with a feedforward controller des...

New results on VRFT design of PID controller

Virtual reference feedback tuning (VRFT) design method can be applied to determine the parameters of a PID controller from the available process input and output data without resorting to the identification of a process model. Although it is an attractive alternative to the popular model-based controller design methods, the existing results are restricted to the linear systems. In this paper, an adaptive VRFT design method with application to the adaptive PID controller design is proposed. In addition, the relationship between the VRFT and IMC designs is analyzed as well. Simulation results are presented to illustrate the advantage of the adaptive VRFT design over the conventional VRFT design.

Nonlinear Control Design Using VRFT

In this paper, a design method of nonlinear controllers is proposed. While physical or chemical analysis is a reliable approach for the construction of nonlinear models, it needs many experiences and might result in very complicated models. The Black-box model approach is adopted in this paper. Identification and controller design of nonlinear processes are very troublesome and complicated. Therefore, a direct design method of nonlinear control, which means not to identify process models, is proposed. The controller is designed using the idea of VRFT (virtual reference feedback tuning). In order to deal with the nonlinearity, input–output data in various operating conditions must be obtained. However, it is very difficult to get sufficient quantities of data for identification of the nonlinearity. Therefore, the model reliability should be evaluated. If the operating condition was not included in the learning data for the nonlinear model identification, the reliability of the model should be judged low. In such a case, it is proposed to suppress the magnitude of the manipulation change. Moreover, in such a case, the online data are stored and are used to re-design the nonlinear model offline. The effectiveness of the proposed controller was shown in a simulation of a tank system.

Integrating virtual reference feedback tuning into a unified closed-loop identification framework

This paper compares particular instances of control-relevant identification, closed-loop identification, and controller identification (either in an actual loop or in a virtual reference feedback tuning approach, VRFT) problems. Significant similarities appear between them which allow, in particular, alternative formulations of the VRFT methodology in a differentiable setting.