Showing papers on "Proportional control published in 2020"

Robust Predictive Torque Control of N *3-Phase PMSM for High-Power Traction Application

Abstract: The permanent magnet synchronous motor (PMSM) has become a core component of electromechanical energy conversion in the modern industrial field. In order to expand the application of the PMSM in the field of high-power traction, a robust predictive torque control (R-PTC) strategy for the N -segment three-phase PMSM ( N *3-phase PMSM) is proposed in this article. First, the output characteristics of the N *3-phase PMSM are illustrated with the finite-element analysis method, and the mathematical model is established. Then, the six-segment three-phase PMSM predictive control system driven by six parallel inverters is designed to generate the required torque. Furthermore, the influence of the parameter mismatch on the predicted torque and stator flux is taken into consideration based on the conventional predictive torque control (PTC). Finally, a novel R-PTC method with the proportional controller is developed for the N *3-phase PMSM, which can effectively improve the accuracy and robustness of predictive control performance under the parameters mismatch. The simulation and experimental results verify that, compared with the conventional PTC, the proposed R-PTC method can make the predicted stator flux and torque value accurately track its reference values while achieving lower stator flux and torque ripple.

Robust Quasi-Predictive Control of $LCL$ -Filtered Grid Converters

Abstract: This paper proposes a new control strategy for grid-connected $LCL$ -filtered voltage source converters (VSCs). It is realized by cascading a proportional-resonant (PR) controller, which regulates the grid-side current, and a finite-set model predictive controller (FS-MPC), which is responsible for controlling the filter's capacitor voltage and active damping of the resonance. The overall control circumvents the drawbacks of using only the FS-MPC to control the converter, such as steady state tracking error, weighting factor tuning complexity, and need to use long prediction horizons for optimal performance, but it keeps its advantageous properties. Namely, due to FS-MPC's direct manipulation of the VSC switches, the pulsewidth-modulation delay does not exist, while a high sampling rate leads to only insignificant computational delay. As a consequence, the system achieves far less magnitude and phase roll-off in the high-frequency region that allows considerable increase of dynamic performance compared to conventional control approaches. Moreover, the inner FS-MPC-based regulator exhibits a flat frequency response, which indicates that there is no need for designing a dedicated AD. The overall control design procedure is then largely simplified as only the proportional gain of the PR controller needs to be tuned. These properties are proved using a describing function method where a linear approximation of the FS-MPC regulated VSC and an inner $LC$ filter is derived in the frequency domain and integrated together with the model of the PR controller and grid side inductor. The controller has been analyzed analytically and validated through experimental results, where design correctness and robustness to grid-side inductance variations have been tested.

Stabilization parametric region of distributed PID controllers for general first-order multi-agent systems with time delay

Abstract: The stabilization problem of distributed proportional-integral-derivative ( PID ) controllers for general first-order multi-agent systems with time delay is investigated in the paper. The closed-loop multi-input multi-output ( MIMO ) framework in frequency domain is firstly introduced for the multi-agent system. Based on the matrix theory, the whole system is decoupled into several subsystems with respect to the eigenvalues of the Laplacian matrix. Considering that the eigenvalues may be complex numbers, the consensus problem of the multi-agent system is transformed into the stabilizing problem of all the subsystems with complex coefficients. For each subsystem with complex coefficients, the range of admissible proportional gains is analytically determined. Then, the stabilizing region in the space of integral gain and derivative gain for a given proportional gain value is also obtained in an analytical form. The entire stabilizing set can be determined by sweeping proportional gain in the allowable range. The proposed method is conducted for general first-order multi-agent systems under arbitrary topology including undirected and directed graph topology. Besides, the results in the paper provide the basis for the design of distributed PID controllers satisfying different performance criteria. The simulation examples are presented to check the validity of the proposed control strategy.

An Effective Wind Speed Estimation Based Extended Optimal Torque Control for Maximum Wind Energy Capture

Abstract: Most variable-speed wind turbines employ advanced control scheme to improve their performance. In this paper, an extended optimal torque controller is designed based on effective wind speed estimation to control the variable-speed wind turbine. To do this, multilayer perceptron based nonlinear input-output mapping is firstly used for approximating the nonlinear aerodynamics of the wind turbine. In other words, based on this nonlinear mapping, effective wind speed is estimated from the measured rotor speed, the measured pitch angle, and the observed aerodynamic torque by the disturbance observer. After that, the optimal rotor speed command for capturing maximum wind energy is derived from the estimated effective wind speed. And then the optimal torque command is calculated by combing the standard optimal torque formula and a proportional control loop that is added to effectively reduce the moment of inertia. At last, some simulation results are validated to display the availability of the improved effective wind speed estimation algorithm and control strategy. Moreover, the corresponding simulation results indicate that compared with the existing methods, the proposed method increases the accuracy of the effective wind speed estimation by 2-7% and the energy production efficiency by 0.35%.

PID Controller Autotuning Design by a Deterministic Q-SLP Algorithm

Abstract: The proportional integral and derivative (PID) controller is extensively applied in many applications. However, three parameters must be properly adjusted to ensure effective performance of the control system: the proportional gain (KP), integral gain (KI) and derivative gain (KD). Therefore, the aim of this paper is to optimize and improve the stability, convergence and performance in autotuning the PID parameter by using a deterministic Q-SLP algorithm. The proposed method is a combination of the swarm learning process (SLP) algorithm and Q-learning algorithm. The Q-learning algorithm is applied to optimize the weight updating of the SLP algorithm based on the new deterministic rule and closed-loop stabilization of the learning rate. To validate the global optimization of the deterministic rule, it is proven based on the Bellman equation, and the stability of the learning process is proven with respect to the Lyapunov stability theorem. Additionally, to demonstrate the superiority of the performance and convergence in autotuning the PID parameter, simulation results of the proposed method are compared with those based on the central position control (CPC) system using the traditional SLP algorithm, the whale optimization algorithm (WOA) and improved particle swarm optimization (IPSO). The comparison shows that the proposed method can provide results superior to those of the other algorithms with respect to both performance indices and convergence.

Suboptimal adaptive Kalman filtering based on the proportional control of prior error covariance.

Abstract: For linear time-invariant systems, this paper develops a new kind of adaptive Kalman filter to deal with Kalman filtering problems troubled by unknown/inaccurate process noise covariance. The limitation of Kalman filter is that its performance would deteriorate or even degrade if the accurate noise statistics could not be obtained in advance. To reduce or mitigate the negative influence caused by unknown/mismatched process noise covariance, this work elaborates a novel covariance control scheme in which the prior error covariance is recursively regulated with the proportional form of feedback information: the posterior sequence is first evaluated as online feedback to constitute a closed-loop structure for covariance propagation process, and then a proportional gain is employed to amplify the feedback term and fasten the converging of the estimated covariance parameter; note that, the new approach is relatively more independent of the parameter of process noise covariance and, therefore, the Kalman theory's rigorous dependency on accurate process noise covariance could be relaxed significantly. The mathematical properties and sub-optimality of the new covariance control scheme are discussed in detail as well as some practical considerations. The advantage of this newly developed method in filtering accuracy, adaptability and simplicity are illustrated with an object tracking scenario.

Autonomous Control of a Line Follower Robot Using a Q-Learning Controller.

Abstract: In this paper, a MIMO simulated annealing SA based Q learning method is proposed to control a line follower robot. The conventional controller for these types of robots is the proportional P controller. Considering the unknown mechanical characteristics of the robot and uncertainties such as friction and slippery surfaces, system modeling and controller designing can be extremely challenging. The mathematical modeling for the robot is presented in this paper, and a simulator is designed based on this model. The basic Q learning methods are based pure exploitation and the epsilon-greedy methods, which help exploration, can harm the controller performance after learning completion by exploring nonoptimal actions. The simulated annealing based Q learning method tackles this drawback by decreasing the exploration rate when the learning increases. The simulation and experimental results are provided to evaluate the effectiveness of the proposed controller.

The influence of rate limit on proportional-integral controller for first-order plus time-delay systems.

Abstract: The control performance can be worsened by actuator rate limit, which can result in amplitude attenuation and phase delay in process control. In some extreme situations, actuator rate limit may bring about the system non-convergence. This paper focuses on the control difficulties and solutions of first-order plus time-delay (FOPTD) systems caused by rate limit. The influence of rate limit on stability regions of proportional–integral (PI) controller is analysed. Results show that a small rate limit value can reduce stability regions of PI parameters greatly. The negative correlation between the integral gain and the onset frequency, and the positive correlation between the proportional gain and the onset frequency are conducted. Moreover, the control performance of different PI tuning rules such as Skogestad internal model control, integral gain maximization, delay robustness-constrained optimization and Tyreus–Luyben​ tuning rules is evidently affected by rate limit. Simulation and experiment results verify that the PI controller tuned by Skogestad internal model control (SIMC) method is less sensitive to the rate limit variation and is more suitable for processes (the normalized dead-time is from 0.03 to 1) which have severe actuator rate limit. Tyreus–Luyben tuning rule is another optional method. In addition, the reasons why SIMC is not sensitive to rate limit variation are analysed. These analytical results can offer a guideline for practical applications.

Mitigation of vortex-induced vibration lock-in using time-delay closed-loop control

Abstract: We investigate the closed-loop control of a circular cylinder showing lock-in phenomena due to vortex-induced vibrations (VIV). The control action was implemented by a sampled-data proportional-integral-derivative (PID) controller to suppress the large amplitudes due to lock-in. The controller was first applied to a linearized system to observe its stability characteristics based on the eigenvalues of the system. Another method was also proposed, which employs a novel, time-dependent Lyapunov function that is positive definite at sampling times but not necessarily between the sampling times. A new set of sufficient conditions in terms of linear matrix inequalities is derived to obtain the sampled-data PID control gains for the VIV system. The PID controller tuned with these gains for various delays was applied to control the nonlinear responses of the circular cylinder during the lock-in. The results showed that the PID controller significantly reduced the rise in lock-in amplitude compared to only proportional control and for certain delays was able to completely mitigate the effects of lock-in. It was also observed that for delays ranging from 0.1 to 0.14 s, the nonlinear system was destabilized with increasing proportional gains as indicated by the eigenvalue analysis of the linearized system. Even under such situations, properly tuned integral and derivative gains could significantly reduce the amplitude rise otherwise observed due to lock-in of the uncontrolled system. Finally, an on-off control scheme was also proposed, which, if optimized properly, can restrict the lock-in amplitude to some prescribed limit by only using the control for some fraction of the total operational time. Thus, it can potentially save control power.

Control of DC Motor Using Proportional Integral Derivative (PID): Arduino Hardware Implementation

Abstract: The research proposes controlling DC motor angular speed using the Proportional Integral Derivative (PID) controller and hardware implementation using a microcontroller. The microcontroller device is Arduino Uno as data processing, the encoder sensor is to calculate the angular speed, and the motor driver is L298. Based on the hardware implementation, the proportional controller affects the rise time, overshoot, and steady-state error. The integral controller affects overshoot and undershoot. The derivative controller affects overshoot insignificantly. The best parameter PID is Kp=1, Ki=0.3, and Kd=0.1 with system response characteristic without overshoot and undershoot. Using various set point values, the controller can make the DC motor reach the reference signal. Thus, the PID controller can control, handle, and stabilize the DC motor system.

Motor DC PID System Regulator for Mini Conveyor Drive Based-on Matlab

Abstract: The goal of the research was to develop a Proportional Integral Derivative (PID) control DC motor system as a Matlab-based driver mini conveyor to discover how to regulate speed on an actual mini conveyor where certain factors that impact the research are not considered 0. The hardware configuration of the mini conveyor used hollow steel as a frame and two copies of the roller belt for the stretch belt conveyor. The PID control system used an empirical approach to get the DC motor's response system to determine the best fit of proportional gain, integral gain and derivative gain, and then implement those PID control systems using Matlab and Arduino as the tools for data acquisition. The speed sensor (Rotary Encoder) was mounted on the roller belt to accurately gain read speed. This sensor will submit data on every increasing in PWM to accurately measure the speed and control speed at the same time, based on the set points. The consequence of this work was the proportional gain values = 0.94624747, the Integral gain = 51.4023958 and the derivative gain = 0.01941504. The PID control, designed to monitor the response of motor DC speed on this research, had successfully reached set point value and decreased steady state error from 47.16 percent to 1.015188 percent (unloaded) and 2.2020751 percent (loaded) on the real response device.

Controlling of Pneumatic Muscle Actuator Systems by Parallel Structure of Neural Network and Proportional Controllers (PNNP)

Abstract: This article proposed a novel controller structure to track the non-linear behavior of the pneumatic muscle actuator (PMA), such as the elongation for the extensor actuator and bending for the bending PMA. The proposed controller consists of a neural network (NN) controller laid in parallel with the proportional controller (P). The parallel neural network proportional (PNNP) controllers provide a high level of precision and fast-tracking control system. The PNNP has been applied to control the length of the single extensor PMA and the bending angle of the single self-bending contraction actuator (SBCA) at different load values. For further validation, the PNNP has been applied to control a human-robot shared control system. The results show the efficiency of the proposed controller structure.

Output feedback controller for trajectory tracking of robot manipulators without velocity measurements nor observers

Abstract: The main contribution of this study is the design of a trajectory tracking controller using output feedback applied to robot manipulators. The given controller does not need velocity measurements for its implementation and to achieve the tracking control objective. The structure of the proposed scheme consists of a proportional gain plus a dynamic gain resulting from a first-order system. The dynamic gain is not motivated by any observer nor estimator to approach the joint velocity. The dynamic linear controller has three tunable gain parameters for the one degrees-of-freedom (DOF) systems and two gain matrices for the nDOF lagrangian systems. These gains can be tuned following the conditions given in the stability analysis. An adaptive estimator of the viscous friction coefficient is added to robustify the closed-loop design; the analysis for the estimator is presented for one DOF systems and nDOF manipulators. The closed-loop stability analyses are developed by using Lyapunov's theory. The performance of the proposed control structure is illustrated and compared with other controllers such as the PID controller and the first-order sliding mode algorithm via numerical simulations. Moreover, real-time experiments are carried out in a two DOF SCARA robot manipulator.

Robustness Analysis of Long-Horizon Direct Model Predictive Control: Induction Motor Drives

Abstract: Model predictive control (MPC) requires an accurate system model to achieve favorable performance. Thus, in presence of disturbances, model uncertainties and mismatches, MPC needs tools that provide high degree of robustness to them. Since MPC is, essentially, a proportional control technique, an effective method to deal with the aforementioned issues is the addition of an integrating element to the control scheme. This paper presents a prediction model that introduces an integrator to the control strategy without increasing the size of the optimization problem. To examine its effectiveness, the sensitivity of the classical and the proposed MPC to parameter deviations are discussed and analyzed, considering a wide range of switching frequencies as well as prediction horizon lengths. The robustness examination is performed based on an industrial case study, namely a medium voltage induction motor drive.

Control of closed-loop differential drive mobile robot using forward and reverse Kinematics

Abstract: A “Go-to-Goal” differential-drive mobile robot, in an obstacle-free environment, has been designed and developed in this experiment. The robot is capable of moving in any direction in a 2D Cartesian plane by individually controlling the speed of both driving wheels. The robot can estimate its current position at any point in time. Forward kinematics is applied to estimate the current state of the robot, and reverse kinematics is used in achieving the goal position in the 2D Cartesian plane. A proportional controller is used to control the speed of the wheels for better maneuverability. Effectiveness of the model is tested in both real and ideal conditions. With increasing applications of mobile robots in various fields, this experiment is conducted to test and verify the applied kinematics model. Implementation is by means of a 64-bit microprocessor for processing and an 8-bit dedicated microcontroller for motor control.

Adaptive Visual Regulation of Wheeled Mobile Robots: a Switching Approach

Abstract: This paper deals with the visual regulation problem of wheeled mobile robots (WMRs) in the presence of uncalibrated camera-to-robot parameters and unknown image depth. A two-stage controller is designed by using a switching approach. Specifically, in the first stage, an invariant-manifold-based adaptive controller is presented to bring the lateral error and angular error within an arbitrarily small neighborhood of zero; in the second stage, the longitudinal error is regulated by employing a proportional controller. Utilizing the Lyapunov stability analysis, the exponentially bounded stability of the closed-loop system is proved. Both simulation and experimental results are presented to validate the effectiveness of the proposed approach.

NewtonianVAE: Proportional Control and Goal Identification from Pixels via Physical Latent Spaces

Abstract: Learning low-dimensional latent state space dynamics models has been a powerful paradigm for enabling vision-based planning and learning for control. We introduce a latent dynamics learning framework that is uniquely designed to induce proportional controlability in the latent space, thus enabling the use of much simpler controllers than prior work. We show that our learned dynamics model enables proportional control from pixels, dramatically simplifies and accelerates behavioural cloning of vision-based controllers, and provides interpretable goal discovery when applied to imitation learning of switching controllers from demonstration.

Feedforward Plus Feedback Control of an Electro-Hydraulic Valve System Using a Proportional Control Valve

Abstract: The output feedback signal of the electro-hydraulic valve system (EHVS) affects the activation of its right or left envelope function; thus, even weak measurement noise can cause high-frequency switching between the two envelope functions, leading to chattering in the control input. Consequently, feedforward and feedback controllers in a cascaded configuration generate undesirable chattering in the output signal. We propose a practical and reliable control approach for an EHVS actuated by a proportional control valve. The proposed controller has a parallel structure comprising an inverse generalized Prandtl–Ishlinskii (P–I) model-based feedforward controller, with both hydraulic dead-zone and flow saturation limits, for compensating asymmetric hysteretic behavior. Further, the proposed controller comprises a robust proportional-integral-derivative (PID) feedback controller for achieving robustness against disturbances and noises. The proposed parallel structure is independent of the output feedback of the EHVS. Moreover, the proposed robust PID feedback controller guarantees EHVS stability by precisely selecting the cutoff frequency for the sensitivity and complementary sensitivity functions based on the amplitude spectrum of the inverse-model-based feedforward compensation error. The results verify the high reliability of the proposed EHVS control scheme for the precise control of an EHVS actuated by a proportional control valve in practice.

Skid-Proof Operation of Wheel Loader Based on Model Prediction and Electro-Hydraulic Proportional Control Technology

Abstract: Wheel loader shovel loading operation tests showed that when the tire slips, it not only causes waste of the engine power, but also increases the tire wear. In this paper, the regression prediction model is combined with the electro-hydraulic proportional control technology. For the first time, the method of adjusting the posture of the working device is proposed to realize the skid-proof shovel control strategy of the wheel loader. In this control strategy: (1) The electro-hydraulic proportional control technology applied to this wheel loader is introduced. (2) The load spectrum of the wheel loader is analyzed during the shovel loading operation. Moreover, combined with the drive shaft torque, pilot pressure and boom cylinder displacement, the particle swarm optimization-support vector machine (PSO-SVM) algorithm is used to complete the construction of the regression prediction model of the boom cylinder displacement. (3) A controller is designed based on the fractional-order PID control algorithm. The skid-proof control strategy is simulated and verified by constructing the joint simulation model. The corresponding program is prepared in the hydraulic system controller and the effectiveness of the control strategy and algorithm are verified by the wheel loader shovel loading operation.

Practical torque tracking control of electro-hydraulic load simulator using singular perturbation theory.

Abstract: Nonlinear and high-order characteristics could directly hinder the application of many advanced control algorithms for electro-hydraulic system which is a coupling system with double-dynamics of mechanical and hydraulic components. In this paper, a practical torque tracking control using singular perturbation theory is proposed for electro-hydraulic load simulator. The system model is transformed into a singularly perturbed form including a slow mechanical system and a fast hydraulic system. To achieve high accuracy and strong robustness, an active disturbance rejection control based on desired model compensation is developed for the slow mechanical system. It is proved that the mechanical system with developed slow controller is exponentially stable. A proportional control law is employed for the fast hydraulic system. This hydraulic system with developed fast controller is demonstrated to be exponentially stable. Stability of the whole closed-loop system is theoretically analyzed using the extended Tikhonov's theorem. Experimental results validate the presented control scheme.

Intelligent Operation of Wheel Loader Based on Electrohydraulic Proportional Control

Abstract: In this paper, the wheel loader with electrohydraulic proportional control technology is used as the carrier. For the first time, the dual-angle sensor is used for intelligent operation, which allows the wheel loader working device to be precisely controlled. First, the theoretical analysis of the electrohydraulic proportional control technology on the wheel loader studied in this paper is carried out. Next, according to the feedback of the boom and bucket angle sensor signals, the electrohydraulic proportional control technology is used to initially realize the boom memory and bucket automatic levelling function of the wheel loader working device. Finally, the data acquisition equipment is connected to provide experimental verification, although the test results did not achieve precise control of the working device. After analysis, the detected problems were solved by constructing a neural network algorithm model, which successfully realizes the intelligent and precise operation of the wheel loader, reducing unnecessary energy loss.

Duty Ratio Stability and Average Steady-State Error of Two-Level Current-Mode Wide-Bandwidth Switching Power Amplifiers

Abstract: Nowadays, high-frequency switching power amplifiers (SPA) have been studied widely; bulk of the researches were focused on audio power amplifiers. In active magnetic bearing (AMB) systems, high-frequency electromagnetic excitation caused by rotor imbalance can affect the performance of the SPA, so the traditional SPA cannot meet the requirements of the AMB systems. Therefore, on the premise of ensuring larger power, the frequency of the SPA should be improved to ensure the normal operation of the AMB system. Two-level pulsewidth modulation (PWM) current-mode SPAs are widely used in AMB systems. In order to broaden the bandwidth and to reduce the average steady-state error current, SiC power devices based SPA with a high bus voltage and a high switching frequency was designed. The basic principle and the linearized control model of SPAs are introduced. Then, the duty ratio stability and average steady-state error current of the SPAs are analyzed based on the output ripple current. When the PWM modulator is designed by either the discrete devices or the integrated chips, the critical gains to ensure the duty ratio stability are, respectively, analyzed based on the slope matching and the nonideal characteristic of operational amplifiers. Hence, two methods to reduce the average steady-state error current are proposed, respectively. One is to adjust the offset voltage of triangular carrier for the P controller, the other is to use a proportional integral (PI) controller. The offset adjusting method allows the SPA to achieve better dynamic performance and wider bandwidth. The proportional integral (PI) controller can reduce the average steady-state error current but narrows the bandwidth. Finally, the experiment results are in good agreement with the theoretical analyses.

Basics of PID Control

Abstract: This chapter introduces the basic ideas of proportional integral derivative (PID) control systems. There are four types of controllers that belong to the family of PID controllers: the proportional controller, the proportional plus integral controller, the proportional plus derivative controller and the PID controller. To understand the roles of the controllers, the chapter discusses each of the structures and the PID controller parameters. From the discussions, it establishes some basic knowledge about how to use these controllers in various applications. The chapter then discusses the classical tuning rules that have existed for the past several decades and have withstood the test of time. Next, it discusses the PID controller tuning rules that are derived based on a first order plus delay model. These tuning rules worked well in applications. Several examples are presented for evaluation of the tuning rules that are based on the first order plus delay model.

Application of D-Decomposition Technique to Selection of Controller Parameters for a Two-Mass Drive System

Abstract: In this work, issues related to the application of the D-decomposition technique to selection of the controller parameters for a drive system with flexibility are presented. In the introduction the commonly used control structures dedicated to two-mass drive systems are described. Then the mathematical model as well as control structure are introduced. The considered structure has only basic feedbacks from the motor speed and PI type controller. Due to the order of the closed-loop system, the free location of the system’s poles is not possible. Large oscillations can be expected in responses of the plant. In order to improve the characteristics of the drive, the tuning methodology based on the D-decomposition technique is proposed. The initial working point is selected using an analytical formula. Then the value of controller proportional gain is decreasing, until the required value of overshoot is obtained. In the paper different advantages of the D-decomposition technique are presented, for instance calculation of global stability area for the selected gain and phase margin, the impact of parameter changes, and additional delay evident in the system. Theoretical considerations are confirmed by simulation and experimental results.

Current Control and Active Damping for Single Phase LCL-Filtered Grid Connected Inverter

Abstract: LCL filter has been widely used in the grid connected inverter, since it is effective in attenuation of the switching frequency harmonics in the inverter. However, the resonance in this filter causes stability problems and must be damped effectively to achieve stability. There are some methods to damp the resonance; one method is passive damping of resonance by adding a series resistor with the filter capacitor, but passive element reduces the inverter efficiency. Other method uses active damping (AD) by adding a proportional control loop of filter capacitor current, but this method needs additional sensor to measure filter capacitor current; moreover, when the control loops are digitally implemented, the computation delay in AD control loop will lead to some difficulties in choosing control parameters and maintaining system stability. This paper presents current control scheme for the grid connected inverter with the LCL filter. The proposed scheme ensures the control of injected current into grid with AD of the resonance in the LCL filter while keeping system stability and eliminating the effect of computation delay of the AD loop. An estimation of filter capacitor current with one step ahead is performed using the discrete time observer based on measuring the injected current. This reduces the cost and increases the robustness of the system. Proportional Resonant (PR) controller is used to control the injected current. Design of control system and choosing its parameters are studied and justified in details to ensure suitable performance with adequate stability margins. Simulation and experimental results show the effectiveness and the robustness of the proposed control scheme.

PI parameter influence on underfloor heating energy consumption and setpoint tracking in NZEBs

Abstract: In rooms with underfloor heating (UFH), local on–off controllers most often regulate the air temperature with poor accuracy and energy penalties. It is known that proportional–integral (PI) controllers can regulate most processes more precisely. However, hydronic UFH systems have long time constants, especially in low-energy buildings, and PI parameters are not easy to set manually. In this work, several potential PI parameter estimation methods were applied, including optimizing the parameters in GenOpt, calculating the parameters based on simplified models, and tuning the parameters automatically in Matlab. For all found parameter combinations, the energy consumption and control precision were evaluated. Simpler methods were compared to the optimal solutions to find similar parameters. Compared with an on–off controller with a 0.5 K dead-band, the best PI parameter combination found was with a proportional gain of 18 and an integration time of 2300 s, which could decrease the energy consumption for heating by 9% and by 5% compared with default PI parameters. Moreover, while GenOpt was the best method to find the optimal parameters, it was also possible with a simple automatic test and calculation within a weekend. The test can be, for example, 6-h setbacks applied during the nights or weekend-long pseudo-random changes in the setpoint signal. The parameters can be calculated based on the simplified model from these tests using any well-known simple method. Results revealed that the UFH PI controller with the correct parameters started to work in a predictive fashion and the resulting room temperature curves were practically ideal.