José David Rojas

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

Abstract 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.

Data-driven robust PID tuning toolbox

Abstract 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.

A comparison of bio-inspired optimization methodologies applied to the tuning of industrial controllers

A comparison of different bio-inspired methods is presented for the problem of tuning the parameters of a PID industrial controller for second order plus time delay plants. The compared algorithms are representative of three different kind of methodologies (evolutionary, swarm-based and ecology-based). Al methods are briefly explained and are fully implemented to solve the control problem at hand. It was found that all methods are well suited to solve the problem, but they differ in its computational cost. However in all cases, the different methodologies tested were able to find similar minimum values for different families of plants.

Robustness/performance tradeoff for anisochronic plants with two degrees of freedom PID controllers

In this paper, the anisochronic model (which is able to represent both over-damped and under-damped process with the same topology) is used for the tuning of PI and PID controllers. The relationship between robustness and performance is analyzed for a wide range of model parameters and a tuning procedure is proposed. Then, the performance of the PID controller tuned with the anisochronic model is compared with other tuning methods. It was found that, not only the anisochronic model is well suited for robust tuning of the controller, but it is able to give better performance than other tuning rules, specially if the plant has high order.

Comparison of multi-objective optimization methods for PI controllers tuning

In this work, an analysis of multi-objective optimization methods for PI controllers tuning is presented using the Pareto front concept. A new multi-objective method is proposed to find an evenly spaced Pareto frontier which, at the same time, gives the user an idea of the degradation of one of the objective functions. The results are analyzed from a control theory perspective, which include the comparison with classical PI tuning methods.

Pareto-based polynomial tuning rule for 2DoF PID controllers for time-delayed dominant processes with robustness consideration

A novel polynomial tuning rule is proposed for second order plus time delay system where the time delay is dominant with respect to the time constant. The controller used is a two degrees of freedom PID controller. The rule was found by a curve fitting procedure over data obtained from a series of Pareto optimization with the robustness of the controlled system as constraint. It was found that the proposed methodology is versatile in the sense that, the control engineer is able to choose the allowed degradation of the performance of the system from three different sources of disturbances (set-point changes, input disturbances and output disturbances). The method is compared to the uSORT2 tuning, showing excellent performance results.

Impact of Rooftop PV Integration in Distribution Systems Considering Socioeconomic Factors

This paper presents a methodology to realistically assess the impact of rooftop photovoltaic systems in large-scale distribution networks. The proposed methodology sensibly assigns a photovoltaic capacity and probability of installation to each customer in the network before running the impact assessment. The study makes use of geographic information systems to model the network in detail, including hundreds of secondary systems and thousands of residential and commercial customers. Extensive simulations with different photovoltaic penetrations show that, contrary to simplified adoption models, the proposed methodology can capture the effects of clusters of customers with high probability of installing photovoltaic systems.

Multi-objective design of industrial controllers

The design of industrial controllers with a proportional - integral - derivative (PID) control algorithm can be posing as a multiple-objective optimization problem in case that more than one source of disturbance is taken into account. There are several methodologies to convert this problem into a single cost function optimization. In this work, the Enhanced Normalized Normal Constraint method is applied for optimization of two-degree-of freedom PID controller parameters. The methodology is employed to tune the controller of a LiTaO3 thin film deposition process.

Multi-objective optimal tuning of two degrees of freedom PID controllers using the ENNC method

In this paper the Enhanced Normalized Normal Constrained method is applied to find the optimal tuning of second order PID controllers. This tuning takes into account both the servo and regulatory modes simultaneously, as well as a closed loop robustness criterion. The methodology is successfully applied to a high order linear plant and to a non linear continuous stirred tank reactor model, showing the effectiveness of the optimization methodology to solve control related problems. Also, the method is applied to a benchmark control system that takes into account three different sources of disturbances.

Model reference PI controller tuning for Second Order Inverse Response and Dead Time Processes

In this paper, a One-Degree-of-Freedom PI controller is optimized using the model reference tuning approach for a Second Order Inverse Response and Dead Time Process operating as a servo control. In addition, a graphic user interface tool that computes the PI optimized controller parameters is presented, also showing the response of the control system operating as a servo-control (the optimized one) and the associated response for the regulatory-control case.