PI-type Controller Research Articles

Design and experimental validation of a high voltage ratio DC/DC converter for proton exchange membrane electrolyzer applications

This paper deals with hydrogen production via water electrolysis, which is considered the most attractive and promising solution. Specifically, the use of renewable energy sources, such as wind electric power generators, is hypothesized for supplying the electrolyzer, aiming to strongly reduce the environmental impact. In particular, micro-wind energy conversion systems (μWECSs) are attractive for their low cost and easy installation. In order to interface the μWECS and the electrolyzer, suitable power conditioning systems such as step-down DC-DC converters are mandatory. However, due to the requested high conversion ratio between the DC bus grid, i.e. the output of a three-phase diode rectifier connected to the output of the electric generator, and the rated supply voltage of the electrolyzer, the classic buck converter alone is not suitable. Therefore, a converter is proposed and designed, consisting of a buck converter, a full-bridge IGBT converter, a single-phase transformer, and a diode bridge rectifier; LC filters are also included between buck and full-bridge converters, and at the output of the diode bridge rectifier with the aim of reducing the ripple on currents and voltages. The components of the described physical system from the output of the three-phase rectifier up to the electrolyzer are then modeled assuming the transformer as ideal, and the model is employed for designing a PI-type controller. Experimental results are provided in order to demonstrate the effectiveness of the developed converter and its control for these applications.

Robust trajectory control of an unmanned aerial vehicle using acceleration feedback

In this work, acceleration feedback is utilised in a hierarchical control structure for robust trajectory control of a quadrotor helicopter subject to external disturbances where reference attitude angles are determined through a nonlinear optimisation algorithm. Furthermore, an acceleration-based disturbance observer (AbDOB) is designed to estimate disturbances acting on the positional dynamics of the quadrotor. For the attitude control, nested position, velocity, and inner acceleration feedback loops consisting of PID and PI type controllers are developed to provide high stiffness against external disturbances. Reliable angular acceleration is estimated through a cascaded filter structure. Simulation results show that the proposed controllers provide robust trajectory tracking performance when the aerial vehicle is subject to wind gusts generated by the Dryden wind model along with the uncertainties and measurement noise. Results also demonstrate that the reference attitude angles calculated through nonlinear optimisation are smooth and within the desired bounds.

Experimental study of radiator, underfloor, ceiling and air heater systems heat emission performance in TUT nZEB test facility

This paper reports the results of different heat emitter system measurements, which were carried out at the nZEB test facility near Tallinn University of Technology in early 2018. Radiators, underfloor heating, air heaters and radiant ceiling panels are studied as coupled with different control schemes ranging from ON-OFF to PI-type control. The objective is to assess and quantify the control accuracy and thermal comfort parameters among different configurations. Scheduled heating dummies are used to simulate internal heat gains within the otherwise unoccupied test rooms. Along with outdoor temperature variation, the heating demand is therefore constantly changing and the control systems are continuously adjusting the heat output to maintain the desired indoor air temperatures. Control accuracy is then determined from the temperature deviations against this set value. Air stratification within the room is assessed with vertical temperature gradient calculations from measured air temperatures at different heights. The operative temperature at the point of expected occupancy is calculated from surrounding air and enclosing surface temperatures. The quantified results provide a comprehensive comparison between the different system configurations, enabling further energy simulations in related software packages since these parameters directly influence the energy usage within a system.

A Study about Performance and Robustness of Model Predictive Controllers in a WEC System

This work is located in a growing sector within the field of renewable energies, wave energy converters (WECs). Specifically, it focuses on one of the point absorber waves (PAWs) of the hybrid platform W2POWER. With the aim of maximizing the mechanical power extracted from the waves by these WECs and reducing their mechanical fatigue, the design of five different model predictive controllers (MPCs) with hard and soft constraints has been carried out. As a contribution of this paper, two of the MPCs have been designed with the addition of an embedded integrator. In order to analyze and compare the MPCs with conventional PI type control, an exhaustive study about performance and robustness is realized through the computer simulations carried out, in which uncertainties in the WEC dynamics and JONSWAP spectrum are considered. The results obtained show how the MPCs with embedded integrator improve power production of the WEC system studied in this work.

ESO-Based Double Closed-loop Servo Control for Automobile Electronic Throttle

A kind of double closed-loop servo control strategy is presented in this paper to realize accurate and fast position tracking of throttle valve for the automobile electronic throttle control system (ETCS). The control structure includes an extended state observer (ESO) compensating for the total disturbances resulted from nonlinearities of friction and return springs and uncertainties of some physical parameters, and two PI-type controllers with disturbance compensators of the outer position loop and the inner current loop. The proposed scheme is featured by transforming the control gains determination for the two PID-type controllers into the derivation of state feedback gains. And the transformation is carried on by means of the augmented deviation equations constructed by the ESO-estimated unmeasurable current and angular velocity of throttle. And control parameters of the two feedback loop controllers and ESO can be instructively determined by solving the linear matrix inequalities (LMIs) obtained from the Lyapunov stability analysis of the whole closed-loop system. The feasibility of the proposed strategy is validated in both simulation and hardware-in-the loop (HIL) test platform.

Adaptive Nonlinear Control of Reduced‐Part three‐Phase Shunt Active Power Filters

AbstractThe problem of controlling reduced‐part three‐phase shunt active power filters is addressed in the presence of nonlinear loads. The control objective is twofold: (i) compensation of the current harmonics and the reactive power absorbed by the nonlinear load in order to ensure a satisfactory power factor correction (PFC) at the grid‐filter connection point; (2) regulation of the DC bus voltage at the inverter input. The considered control problem entails several difficulties including: (1) the high dimension and strong nonlinearity of the system; (ii) the numerous state variables that are inaccessible to measurements; (iii) the system parameter uncertainty. The problem is dealt with by designing a nonlinear adaptive controller with cascade structure including two control loops. The inner‐loop regulator is designed using the Lyapunov technique to ensure the PFC objective, while the outer‐loop involves a linear PI type control law for DC bus voltage regulation. The controller also includes an adaptive observer estimating the grid voltages and impedances parameters. The resulting control performances are formally analyzed using the averaging theory. Simulation results are presented illustrating the performances and the strong robustness of the proposed control strategy.

Water level control of a small hydropower plant with a surge tank

ABSTRACTThis paper presents an application of a small hydropower plant (SHP) embedded in a hydraulic system with a surge tank of a relatively low water volume. To maintain a stable surge tank water level the author used a precisely designed PI-type controller. The analytical design method, the so-called root locus, was used in this work. A new identification method that uses the step response to identify the parameters of a real system is described. The proposed method, analytical models of hydraulic system and turbine as well as water level controller were implemented and tested in a real 55 kW grid connected SHP utilizing treated water from a wastewater treatment plant. The results of the tests conducted under substantial variations of the water flow confirmed the stable operation of the controller at the maximum water level fluctuations of ±5 cm during a normal operation.

Fuzzy PI-type controller design for boost converter

ABSTRACTWe consider the fuzzy controller design problem for a boost DC-DC converter. We design a fuzzy PI-type controller based on the common control engineering knowledge that the transient control performance can be improved if we increase the P and I gains as the error grows. Using Kharitonov’s theorem, we derive a closed-loop control system stability condition which can be used to tune the fuzzy PI control parameters. Finally, we give simulation and experimental results to show the effectiveness and practicality of the proposed method.

Genetic Algorithm based Decentralized PI Type Controller: Load Frequency Control

This work presents a design of decentralized PI type Linear Quadratic (LQ) controller based on genetic algorithm (GA). The proposed design technique allows considerable flexibility in defining the control objectives and it does not consider any knowledge of the system matrices and moreover it avoids the solution of algebraic Riccati equation. To illustrate the results of this work, a load–frequency control problem is considered. Simulation results reveal that the proposed scheme based on GA is an alternative and attractive approach to solve load–frequency control problem from both performance and design point of views.

Decoupled Current-Balancing Control With Single-Sensor Sampling-Current Strategy For Two-Phase Interleaved Boost-Type Converters

For interleaved boost-type converters, both functions of voltage regulation and current balance are important. In this paper, the decoupled current-balancing control (DCBC) with two parallel loops is proposed. At first, the small-signal transfer functions of the voltage-regulation loop and the current balancing loop to the controller output are derived. The results show that the voltage-regulation loop and the proposed current-balancing loop are nominally decoupled. That is, two PI-type controllers can be designed independently and included to implement the proposed DCBC. Additionally, the single-sensor sampling-current strategy is proposed to obtain two average inductor currents by sensing only the sum of diode currents. All the controllers are implemented in field-programmable gate array (FPGA). The provided simulation and experimental results demonstrate the proposed DCBC.

Nonlinear and Robust Control Strategy Based on Chemotherapy to Minimize the HIV Concentration in Blood Plasma

A nonlinear PI-type control strategy is designed in order to minimize the HIV concentration in blood plasma, via medical drug injection, under the framework of bounded uncertain input disturbances. For control design it is considered a simplified mathematical model of the virus infection as a benchmark. The model is based on mass balances of healthy cells, infected cells, and the virus concentrations. The proposed controller contains a nonlinear feedback PI structure of bounded functions of the regulation error. The closed-loop stability of the system is analyzed via Lyapunov technique, in which robustness against system disturbances is demonstrated. Numerical experiments show a satisfactory performance of the proposed methodology as a HIV therapy, in which the virion particles and the infected CD4+T cells are minimized and, as an interesting result, the drug dosage can be suspended, thus avoiding drug resistance from the virus. Finally, the proposed controller is compared to a standard sliding-mode and hyperbolic tangent controllers showing better performance.

IM Direct Torque Control with no flux distortion and no static torque error

The purpose of this paper is to improve DTC control strategy performances. In fact, we propose controlling both stator flux components (real and imaginary) through two hysteresis controllers. Thus, a new switching table which is independent from sector determination, and does not introduce zero voltage vectors is established; with much reduced size when compared to Takahashi's one. The proposed strategy has allowed cutting off with flux and current harmonics related to distortion caused by sector exchanges. Also, we provide theoretical evidence about the existence of static torque error in classical DTC, and propose a simple PI-type controller to cancel it. The proposed strategy is validated by simulation and practically on a DSPace 1104 board, for a 1.5 (kW) induction motor and various torque references.

Anti-disturbance tracking control for systems with nonlinear disturbances using T–S fuzzy modeling

This paper addresses a novel anti-disturbance dynamical tracking problem for a class of MIMO systems subject to unknown disturbances and nonlinear dynamics. Different from some traditional anti-disturbance results, T–S fuzzy models are firstly employed to describe the nonlinear disturbances, in which a disturbance observer based on T–S exogenous models is designed under different conditions to estimate the unknown nonlinear disturbances for the plants with known and unknown nonlinearities, respectively. By integrating the estimates of disturbance with PI-type control input, a composite controller based on convex optimization theory is proposed to ensure the system stability and convergence of the tracking error to zero. Meanwhile, the favorable disturbance estimation and attenuation performance can also be achieved by the designed convex optimization algorithm. Finally, the effectiveness of the proposed control schemes is verified by simulations for flight control systems with three different types of nonlinear disturbances.

Nonlinear Predictive Control of Wind Energy Conversion System Using Dfig with Aerodynamic Torque Observer

Abstract In order to improvement of the performances for wind energy conversions systems (WECS), an advanced control techniques must be used. In this paper, as an alternative to conventional PI-type control methods, a nonlinear predictive control (NPC) approach is developed for DFIG-based wind turbine. To enhance the robustness of the controller, a disturbance observer is designed to estimate the aerodynamic torque which is considered as an unknown perturbation. An explicitly analytical form of the optimal predictive controller is given consequently on-line optimization is not necessary The DFIG is fed through the rotor windings by a back-to-back converter controlled by Pulse Width Modulation (PWM), where the stator winding is directly connected to the grid. The presented simulation results show a good performance in trajectory tracking of the proposed strategy and rejection of disturbances is successfully achieved.

Speed Control of Vector Controlled Induction Motors under Variable Load with RBFNN Based Model Reference Adaptive Control

In the speed control of induction motors, an acceptable good performance cannot be obtained by using traditional feedback controllers due to the non-linear structure of the system, the effects of changing environmental conditions and several disturbance inputs. On the other hand, in recent years, it has been demonstrated that artificial intelligence based control methods were much more successful in the nonlinear system control applications. In this study, an intelligent controller has been developed for speed control of induction motors by using radial basis function neural network (RBFNN) and model reference adaptive control (MRAC) strategy. In the driving of induction motor, indirect field oriented vector control method which is widely used in high-performance drive system has been preferred. Simulation results to determine the success of the development of this control method was compared with conventional PI type controller. While the motor is under the fan-type load, the performance of controller has been investigated in Matlab/Simulink environment. The simulation results demonstrate that the performance of RBFNN based MRAC controller is better than that of conventional PI controller.

Multi Objective Optimization of Multi Component Isothermal Liquid-Phase Kinetic Sequence using Multivariable PI Control

In this paper, an optimal tuned saturated PI type controller with anti-windup structure is used for process control. In first step, a single objective genetic algorithm is used to find the optimal values of controller parameters. To show the difference between optimal and non-optimal control, we use this controller to track the square pulse. The results show that by choosing the control parameters randomly the output cannot track the reference signal but by optimizing the control parameters, the error, and settling time decreases significantly and efficiency of control increases but it needs more control effort. To find the optimal control parameters with lower control input, a multi objective genetic algorithm is used in next step and three points in Pareto front are analysed. It is shown that this method increases the control efficiency and needs lower control input than obtained by single objective genetic algorithm.

Adaptive fuzzy vector control for a doubly-fed induction motor

This paper presents a new adaptive fuzzy vector controller (AFVC) to handle the torque and speed tracking problem of a doubly-fed induction motor (DFIM) as an alternative to classical PI based vector control method generally used for its simplicity. However, the control performance of DFIM is still influenced by the variations of the parameters, the external load disturbances and perturbations in practical applications. Then, it is difficult to achieve high control performances of DFIM by using conventional PI-type control techniques. The proposed AFVC scheme uses adaptive fuzzy systems to reasonably approximate the uncertain dynamics appearing in the DFIM, relaxing thereby the usual modeling requirement about the DFIM dynamics. Of fundamental interest, it is shown that all the closed-loop signals are bounded and the tracking errors exponentially converge to a residual set. Probing simulation results are given to emphasize the effectiveness of the proposed AFVC system with respect to the usual feedback linearization based vector control (FLVC) system.

Fuzzy-Based Controller Design for Intelligent Robot Arm

In this paper, a fuzzy logic-based control system is proposed, which lays emphasis on the functionality of the system rather than developing a mathematical model. Applied to an arm robot, it can achieve precise motion control along with power consumption minimization. Dynamic equations of the physical modeling of a two-arm planar robot were first derived and then a Proportional-Integral (PI) fuzzy logic controller was designed to maintain a desired trajectory of motion. Numerical results show promising performance since the proposed PI-type fuzzy logic controller can be used for trajectory tracking of dual-arm robots during safely load transportation tasks

Blowdown wind tunnel control using an adaptive fuzzy PI controller

The paper presents an approach towards the control of a supersonic blowdown wind tunnel plant (as evidenced by experimental data collected from INCAS Supersonic Blowdown Wind Tunnel) using a PI type controller. The key to maintain the imposed experimental conditions is the control of the air flow using the control valve of the plant. A proposed mathematical model based on the control valve will be analyzed using the PI controller. This control scheme will be validated using experimental data collected from real test cases. In order to improve the control performances an adaptive fuzzy PI controller will be implemented in SIMULINK in the present paper. The major objective is to reduce the transient regimes and the global reduction of the start-up loads on the models during this phase.

Self-Tuning Fuzzy PI-Type Controller in Z-Source Inverter for Hybrid Electric Vehicles

This paper presents new algorithms to control speed induction motor (SIM) and the peak dc-link voltage (PDV) across the inverter bridge in z-source inverters (ZSI) by applying self-tuning fuzzy PI controller (SFP) with robust structure and non-linear characteristic. In particular, this so-called SFP based control algorithm (SFPA) is applied to a closed loop speed control system of induction motor, which relies on direct torque control scheme combined with modified space vector modulation (DTCMSVM) control strategy with so many exceptional features (e.g. fast torque response, low steady state torque ripple, and high accurate). Additionally, SFPA is used to control SIM and PDV are more adaptive to the sudden change of parameters such as load torque, stator resistance and dc input voltage (DIV), respectively. The transient response of SIM and PDV are thus improved with less over shoot, short rise time, small steady-state error and fast settling time, with low disturbance for output voltage stabilization in the inverter bridge. As a result, we achieve higher accuracy and robustness of SIM control system. Our new SFPA is verified in both simulation and experimental implementation using MATLAB and dSPACE DS1103, respectively. DOI: http://dx.doi.org/10.11591/ijpeds.v2i4.571