Implementation Of Control Algorithm Research Articles

Implementation of the lighting control algorithms in the KNX system

There are many different ways of managing the lighting. The usage of appropriately selected controlling algorithms allows to increase the functionality, improve the comfort of using and introduces measurable benefits in the form of power consumption savings. In order to precisely apply the proper lighting control algorithms, it is important to know the distribution of light intensity in the room. This article is aimed at comparing different ways of lighting control and contains a control idea based on the KNX system, which is a popular building automation system. It is very useful for the implementation of lighting control criteria.

Complexity reduction of Model Predictive Control for a de-manufacturing plant

The use of advanced optimization-based techniques will be a fundamental step towards performance enhancement of flexible manufacturing plants. However, the mixed integer nature of the resulting optimization problems and the associated computational issues can represent a bottleneck and a severe limitation to their diffusion. This paper describes the design and efficient implementation of a Model Predictive Control (MPC) algorithm for a de-manufacturing plant. To reduce the computational effort due to the on-line optimization, the main idea is to resort to the so-called control horizon, widely used in classical MPC applications. A heuristic control strategy, requiring a lower computational effort, is first designed. Then, the MPC algorithm is implemented by considering a prediction horizon larger than the control horizon, and assuming that the heuristic rules are used from the end of the control horizon onwards. This significantly reduces the number of optimization variables to be computed through the solution of a Mixed Integer Linear Programming (MILP) problem. Notably, by adopting a rolling horizon strategy, the heuristic rules are never applied in practice. Simulation results are reported to compare the performances of the algorithm here developed, in terms of computational time and plant throughput, to those of a standard MPC problem and of the heuristic rules. These results witness the ability to the developed method to reduce the on-line optimization time without a significant performance reduction with respect to the standard MPC.

A simplified model for friction compensation in precise feed drives

Friction is a complex phenomenon with negative effects on the precision of positioning systems. In this work, a single-state friction model for control purposes, aimed to simplify the implementation of control algorithms while keeping a good performance in friction compensation, is analysed. In particular, the model is capable or representing the Stribeck curve, rate independent presliding hysteresis with non-local memory and non-drifting behaviour. This model has been tested on an experimental setup based on a linear motor, and its performance is compared to that of the generalised Maxwell-slip model, showing better performance on the tracking error.

A simplified model for friction compensation in precise feed drives

Friction is a complex phenomenon with negative effects on the precision of positioning systems. In this work, a single-state friction model for control purposes, aimed to simplify the implementation of control algorithms while keeping a good performance in friction compensation, is analysed. In particular, the model is capable or representing the Stribeck curve, rate independent presliding hysteresis with non-local memory and non-drifting behaviour. This model has been tested on an experimental setup based on a linear motor, and its performance is compared to that of the generalised Maxwell-slip model, showing better performance on the tracking error.

Vision Based Intelligent Vehicle Steering Control Using Single Camera for Automated Highway System

Generally, stereoscope vision is used for guiding autonomous intelligent road vehicles, as image depth can be calculated easily. However, when one of the camera fails, it will advantages to have suitable guidance algorithm that can detect the lane marking using single camera. The primary objective of this work is to develop and implement control algorithms for identifying and guiding the intelligent road vehicle in the assigned lane using image-processing techniques, using single camera. It deals with dividing the video being taken by the camera, into several number of frames. Then, the obtained frames are processed using Image acquisition techniques in Matlab. It detects the lane to be followed through image processing, calculates the angle of movement required for the robot to stay in the assigned path and commands the steering system with appropriate control algorithms. The identification of lane is done using color detection and boundary marking techniques. The image initially undergoes Inverse Perspective Mapping (IPM) for viewing the 3-D space in a 2-dimensional array. Once the IPM of the acquired image undergoes lane detection algorithm, the angle of any curve in the lane is detected using angle detection module. The robot is also made to move at the center of the path using Fuzzy Logic algorithms, where it takes distance from the left detected edge as the input and outputs the angle to be moved by the robot to stay in the center. The developed algorithm has been tested using P3-DX Pioneer mobile in laboratory condition. The experimental result obtained show that the algorithm used by the vehicle to follow the center of the lane, with any given angle or position of initiation, has worked all the times under given experimental conditions, with a maximum error of 2 cm.

Modern methods of design, analysis, optimization and implementation of conventional control algorithms for processes with finite and infinite degrees of freedom

This paper presents characterization methods for a large class of industrial processes using a critical experiment as well asmodern methods of design, analysis, optimization and implementation of conventional control algorithms. Special attention is set to theprocess characterization methods using relay techniques and phase-locked loops in order to form a general process model which servesas a base for adequate controller design. This general process model adequately approximates processes which behaviour can bedescribed with linear mathematical models with finite and infinite degrees of freedom including conventional finite dimension systems,time-delay systems, systems whose behaviour is dominated by a wave and transport problems such as mass and energy transfer,systems described with fractional differential equations etc. Based on characterization, an important accent is also put on the design ofPI/PID controller due to their large application in industry which exceeds 93% compared to all the other controllers according toHoneywell's surveys. In order to illustrate validity of characterization model and effectiveness of presented design method, the paperprovides an example of optimal PID controller designed under constraints on robustness and sensitivity to the measurement noise.Digital implementation is considered for both the controllers with rational and those with non-rational transfer functions. At the end,controller analytical design methods are elaborated and analytical formulae for PI/PID controllers tuning are presented.

Digital Signal Processing in Power Electronics Control Circuits, Second Edition [Book News

This textbook has been revised and extended for its second edition (the first edition was published in 2013). It discusses problems related to the design and implementation of digital control algorithms for power electronics systems using the digital signal processing (DSP) approach. The contents of the book are organized into seven chapters: 1) “Introduction” 2) “Analog Signals Conditioning and Discretization” 3) “Selected Methods of Signal Filtration and Separation and Their Implementation” 4) “Selected Simulation Methods and Programs for Power Electronic Circuits” 5) “Selected Active Power Filter Control Algorithms” 6) “Digital Signal Processing Circuits for Digital Class-D Power Amplifier” 7) “Conclusion and Future Work.” The book opens in Chapter 2 with a discussion on the processing of analog-to-digital (A/D) signals and the most common source of errors. The author presents an overview of A/D converters suitable for power electronics control. Digital filters, multirate circuits, digital filter banks, and microcontrollers for power electronics are discussed in Chapter 3. This second edition includes a new and useful Chapter 4 that presents problems pertaining to the simulation of digitally controlled power electronic systems and includes numerous program listings in MATLAB and PSIM. The next two chapters include descriptions of selected active power filter (Chapter 5) and class-D power amplifier control algorithms (Chapter 6) as well as their implementation, simulation, and experimental results. The book concludes with a summary and a midterm forecast for future research and developments. The contents of the book are easy to read and presented in an interesting way with good illustrations. Each chapter includes an extensive list of references. This book fills a gap between power electronics and digital signal processing. I strongly recommend it to engineering educators, graduate students, and industry engineers who are interested in understanding the design of modern DSP-controlled power electronic systems.

Real-time implementation of a robust active control algorithm for narrowband signals suppression

This study presents a practical active noise control (ANC) algorithm with robust stability for reducing the powertrain noise or vibration inside a car. It is important to ensure that a practical ANC system for a car is robustly stable to variations or uncertainties in the actual plant. After investigating the robust stability condition of the ANC algorithm, a robust plant model is designed by considering the multiplicative plant uncertainties within given bounds such as closing or opening door windows. The ANC algorithm was implemented in a dSPACE DS1401 as a control platform, and an error microphone and a subwoofer as a secondary source were positioned at the driver’s left ear and the trunk of the experimental car, respectively. The engine rpm information received from the controller area network of the car was used for the generation of relevant reference signals. The real-time control experiments were carried out against the plant perturbation when the engine was either idling or sweeping in the neutral mode. The results showed that the robust control algorithm can suppress the noise whether the actual plant was nominal or perturbed with the stability over the rpm.

Resonator reset in circuit QED by optimal control for large open quantum systems

We study an implementation of the open GRAPE (Gradient Ascent Pulse Engineering) algorithm well suited for large open quantum systems. While typical implementations of optimal control algorithms for open quantum systems rely on explicit matrix exponential calculations, our implementation avoids these operations leading to a polynomial speed-up of the open GRAPE algorithm in cases of interest. This speed-up, as well as the reduced memory requirements of our implementation, are illustrated by comparison to a standard implementation of open GRAPE. As a practical example, we apply this open-system optimization method to active reset of a readout resonator in circuit QED. In this problem, the shape of a microwave pulse is optimized such as to empty the cavity from measurement photons as fast as possible. Using our open GRAPE implementation, we obtain pulse shapes leading to a reset time over four times faster than passive reset.

Embedded Software Implementation of the SISO Adaptive Predictive Control Algorithm

Advancements in microelectronic technology provide the opportunity of implementing more complex and computation-heavy algorithms. One area that benefits from these advancements is the automation and control industry. Control techniques and algorithms, previously implemented in industrial and commercial personal computers, are being ported to embedded systems, taking advantage of their real-time and customization capabilities. This work introduces a software-based embedded implementation of a single-input single-output adaptive predictive control (APC) algorithm. The goal of the proposed implementation is to minimize execution time of the APC algorithm without affecting the precision of the results. The ZYBO Zynq-7000 development board was the selected platform for development and evaluation. Our proposed software-centric implementation relies on the development of libraries for matrix data storage and manipulation, and data structures to minimize data transactions. Experimental results included the comparison of APC implementations with different memory usage and data management approaches. An improvement on execution time was possible, reducing it nearly 50% from an initial implementation. Experimental results show no impact on the precision after comparing the implementation results to the results obtained using Scilab-based numerical computation.

Analysis and implement of the single‐phase voltage‐controlled grid‐connected inverter

This study describes the design and implementation of an inverter control algorithm with both the inverter inner controllable impedance and governor-free characteristics. The inverter controlled as a voltage supply works with open-loop power control in grid-connected operation. It is realised that a pulse-width modulation inverter mimics the primary frequency and voltage modulation characterised similarly to a synchronous generator. On the basis of the proposed control algorithm, the inner controllable impedance and governor-free characteristics are analysed mathematically. Simultaneously, the authors analyse the output power characteristics of the proposed inverter and the level of the decoupled power control for designing the inner controllable impedance. When the inverter connects with the stiff grid, it will appear as the output current deviation problem. The generation mechanism of the dc component from the proposed inverter is clearly identified. The current deviation compensation control is analysed and implemented to solve it. Simulations and experimental results are given to verify the idea.

Implementation of LLMF Control Algorithm for Three-Phase Grid-Tied SPV-DSTATCOM System

This paper proposes a three-phase single-stage grid integrated solar photovoltaic distributed static compensator (SPV-DSTATCOM) system using a leaky least mean fourth (LLMF) control algorithm. The prime contributions of this paper include: 1) the SPV generating system, which fulfills the active power requirement of connected loads and supplies the excess power to the grid; 2) the voltage-source converter (VSC) acts as a dc–ac inverter and DSTATCOM, which provides reactive power compensation, harmonics filtering, load balancing, power factor correction, zero voltage regulation, and mitigates several other power quality issues; 3) even when the SPV power is unavailable, the VSC operates as a DSTATCOM, which enhances the utilization factor of devices; and 4) the LLMF-based control approach for fundamental component extraction from load currents for good harmonics compensation as well as to keep the overall system stable and to achieve rapid response at changing conditions. The proposed system is modeled and simulated using MATLAB/Simulink as well as its performance is verified experimentally on a developed prototype.

Time-optimal velocity tracking control for differential drive robots

Nonholonomic wheeled mobile robots are often required to implement control algorithms designed for holonomic kinematic systems. This creates a velocity tracking problem for an actual wheeled mobile robot. In this paper, we investigate the issue of tracking a desired velocity in the least amount of time, for a differential drive nonholonomic wheeled mobile robot with torque inputs. The Pontryagin Maximum Principle provides time-optimal controls that must be implemented as open-loop commands to the motors. We propose two discontinuous state-based feedback control laws, such that the associated closed-loop systems track a desired velocity in minimum time. The feedback control laws are rigorously shown to produce only time-optimal trajectories, by constructing a regular synthesis for each control law. The availability of these time-optimal feedback control laws makes re-computation of open-loop time-optimal controls (due to changes in the desired velocity or input disturbances) unnecessary.

An improved single phase transformerless inverter topology for grid connected PV system with reduce leakage current and reactive power capability

Abstract Single phase transformerless inverters are widely being adopted for small scale grid connected PV systems due to their high efficiency, lower cost and high power density. However, leakage current is the main concern in these inverters which needs to be addressed carefully. Moreover, PV inverters should also be capable of injecting a definite amount of reactive power into the grid as prescribed by the international regulations. In this paper, an improved H6 common mode voltage (CMV) clamped topology with modified modulation strategy is proposed. The proposed topology offers low loss ac side decoupling, complete elimination of leakage current via CMV clamping and reactive power generation capability. The proposed modulation technique facilitates the flow of current in order to generate zero voltage state during negative power flow. Total harmonic distortion (THD) of injected grid current at various solar irradiance levels is also analyzed. Moreover, implementation of inverter control algorithm in real time digital simulator (OP-5600) has been discussed in detail. In order to justify the suitability of the proposed topology for grid-tied PV system, simulations have been carried out in Matlab/Simulink environment and validated through an experimental setup.

Algorithm implementation of traction converter topology based on MFT and single phase matrix converter

This paper presents an implementation of control algorithms of traction converter topology with medium frequency transformer (MFT) using matrix converters intended for locomotives and particularly for suburban units supplied by a 25 kV/50 Hz and/or 15 kV/16.7 Hz AC overhead line. Traction converter consists of input medium voltage matrix converters directly connected to the overhead line and outputs supply MFTs. The proposed traction converter concept with MFT replaces classical topology based on bulky line traction transformer and significantly reduces size and weight of the traction transformer. This paper describes in detail control algorithms and their implementation of the proposed converter configuration. The converter concept with common MFT using coupled magnetic flux for balancing input capacitor voltages and modular concept with separate power cell and individual MFTs have been discussed. The paper analyses in detail the matrix converter commutation based on standard 4-step commutation with respect to knowledge of input voltage polarity or output current polarity. The control algorithms also keep in touch the minimizing of the MFT magnetic saturation at extremely low switching frequency. The behaviour of the proposed converter power circuit has been analysed by simulations and verified by experimental test on developed low-scale functional prototype with rated power up to 4 kVA.

Design and implementation of multichannel global active structural acoustic control for a device casing

Abstract The paper presents the idea and discussion on implementation of multichannel global active noise control systems. As a test plant an active casing is used. It has been developed by the authors to reduce device noise directly at the source by controlling vibration of its casing. To provide global acoustic effect in the whole environment, where the device operates, it requires a number of secondary sources and sensors for each casing wall, thus making the whole active control structure complicated, i.e. with a large number of interacting channels. The paper discloses all details concerning hardware setup and efficient implementation of control algorithms for the multichannel case. A new formulation is presented to introduce the distributed version of the Switched-error Filtered-reference Least Mean Squares (FXLMS) algorithm together with adaptation rate enhancement. The convergence rate of the proposed algorithm is compared with original Multiple-error FXLMS. A number of hints followed from many years of authors’ experience on microprocessor control systems design and signal processing algorithms optimization are presented. They can be used for various active control and signal processing applications, both for academic research and commercialization.

Ip2go: An Interior Point Source Code Generator for Solving Linear-Quadratic Optimal Control Problems

Model predictive control applications have broadened from industrial plants with slow system dynamics to the implementation of control algorithms on low-cost hardware. Ip2go has been developed with the aim of making model predictive control readily accessible on embedded systems. It generates efficient, problem-tailored solvers for optimal control problems. The code generator implements Mehrotra’s predictor-corrector interior-point method with Riccati recursions. It can be applied to quadratic programming problems with linear discrete-time system dynamics and polytopic inequality constraints. Both hard and soft constraints can be implemented. In this paper the features of ip2go, the underlying algorithm, the benefits of code generation and the generation process are set out. The comparison of ip2go-generated solvers to state-of-the-art solvers shows that ip2go can compete in terms of efficiency and code-size. The open and modular design allows all users to amend the generator. The Matlab and based and LGPL licensed C-code generator ip2go is available under https://github.com/fabiankrank/ip2go.

Experimental Identification and Characterization of Multirotor UAV Propulsion

In this paper, an experimental procedure for the identification and characterization of multirotor Unmanned Aerial Vehicle (UAV) propulsion is presented. Propulsion configuration needs to be defined precisely in order to achieve required flight performance. Based on the accurate dynamic model and empirical measurements of multirotor propulsion physical parameters, it is possible to design diverse configurations with different characteristics for various purposes. As a case study, we investigated design considerations for a micro indoor multirotor which is suitable for control algorithm implementation in structured environment. It consists of open source autopilot, sensors for indoor flight, “take off the shelf” propulsion components and frame. The series of experiments were conducted to show the process of parameters identification and the procedure for analysis and propulsion characterization. Additionally, we explore battery performance in terms of mass and specific energy. Experimental results show identified and estimated propulsion parameters through which blade element theory is verified.

Fault‐tolerant electric drive and space‐phasor modulation of flux‐switching permanent magnet machine for aerospace application

This study investigates how to improve the fault tolerance or availability of an electrical drive containing a three-phase 12 stator teeth/10 rotor poles (12/10) the flux-switching permanent magnet machine. In this respect, space-vector modulation and space-phasor modulation will be analysed in this type of machine for control scheme design under three-phase operation. While for safety critical applications, availability requires that during faults, such as loss of one inverter phase leg or open circuit of one machine phase winding, the electrical drive system remains partly operational. Therefore, initial research is given in this study on the implementation of control algorithms that drives the machine under normal condition and preserves the electromagnetic torque under phase open-circuit faults.

Hardware-in-the-loop attitude control via a high-order sliding mode controller/observer

In this study, a hardware-in-the-loop implementation of attitude control algorithms based on high-order sliding mode theory is performed and then both compared in terms of performance and functionality. The spacecraft simulator consists of a free-floating platform hinged on a spherical air-bearing support. In order to compensate for the unreliable performance of the rate gyros, a super-twisting sliding mode observer is incorporated to estimate the angular velocities fed back to the controller unit. The proposed scheme makes full use of novel sliding mode methods to alleviate the chattering effects without increasing the control effort; both controllers and observer are tuned to deal with the saturation of reaction wheels with respect to momentum and its rate. The ab initio simulations compared well with the simulator responses, implying that involved instruments including actuators and sensors have been properly emulated. This also proved that the external disturbances were modeled in a reliable manner. The robustness and effectiveness of the proposed scheme have been validated experimentally under extreme circumstances of disturbances and levels of uncertainties.