Generalized Control Algorithm Research Articles

Control of oils and greases adsorptive recovery in conditions of non-stationarity

In various fields of production and transport, the demand for oils and greases, which are complex substances harmful to the environment, is constantly growing, and their production requires significant financial costs.
 An actual task is the creation of control systems for adsorptive purification of used oils and greases, which will be able to meet the requirements of their regeneration quality in conditions of insufficient information provision and non-stationarity of a significant number of characteristics of the technological system.
 The analysis of properties of raw materials, adsorbent and adsorber from the point of view of the necessary and potentially possible information support was carried out.
 Three main sources of non-stationarity are singled out: periodic arrival of raw material with new properties; random changes in properties of current raw materials and adsorbent; gradual changes of the working surfaces of the adsorber due to interaction with adsorbent and adsorbate. The first source is recognized as the most significant, therefore, two components are provided for the general control algorithm – control in the modes of variable and stable raw materials (significant and non-significant changes in properties of raw materials, respectively).
 For each source of non-stationarity, a corresponding adaptation block for pressure and temperature control systems in adsorber with PI-controllers is proposed. The properties of the substances that will be used to correct controllers tasks and their setting parameters have been determined. A system of individual adaptation blocks interaction in both modes of the general control algorithm has been created.
 For the stable raw materials mode, general view of transfer functions for control channels is given and the adaptive control system structure is proposed with implementation of current identification of the control channel model and calculation of the corresponding PI-controllers setting parameters.
 The obtained results will allow to reduce duration and amplitudes of quality indicators deviations of regenerated substances from the set values, which will increase control system efficiency as a whole. The proposed methods can be applied to those technologies where there is a problem of stabilizing properties of input material flows, in particular, in technologies using secondary raw materials.

ABRF: Adaptive BitRate-FEC Joint Control for Real-Time Video Streaming

Adaptive Forward Error Correction (AFEC) algorithms are proposed to achieve efficient Forward Error Correction (FEC) in Real-Time Communication (RTC). However, current AFEC approaches suffer two key limitations. (1) They do not consider the squeezing effect of redundancy on source bitrate while the squeezing usually happens in real RTC applications with limited bandwidth. (2) They estimate the future packet loss simply, ignoring some critical features of packet loss like randomness and multi-pattern. These drawbacks stop them from providing better Quality of Experience (QoE) in RTC services. We propose ABRF, a general QoE-oriented Adaptive BitRate-FEC joint control algorithm. ABRF makes predictions on the network loss pattern in the coming time and jointly calculates the optimal bitrate-FEC decision based on a QoE model for real-time video streaming. Moreover, ABRF is equipped with a fast adaptation method which helps it generalize across diverse network environments. In terms of Video Multi-method Assessment Fusion (VMAF), experimental results tell that ABRF decreases VMAF degradation caused by packet loss by 68%-95% compared with other AFEC algorithms in real-time video streaming in real-world Internet.

H–H Configuration of Modular EV Powertrain System Based on the Dual Three-Phase BLDC Motor and Battery-Supercapacitor Power Supply System

A modular approach to the construction of electric machines, drive systems, power supply systems is a new direction of modern technology development. Especially, the modular approach is promising for electric vehicles due to such positive aspects as increased efficiency, fault tolerance, overall reliability, safety, enhanced control capabilities, etc. In this work, the modular approach is comprehensively applied to an EV powertrain system, which includes a dual three-phase (DTP) BLDC motor with two machine modules of an asymmetric configuration, two battery modules and a supercapacitor module (SCM). The proposed H–H configuration of modular EV powertrain system includes four voltage source inverters that combine the power modules with the open ends of the windings (OEW) of the module machine armature, and provide control of their operation. Based on the developed mode system of the OEW machine module operation for EV traction and braking, a general control algorithm for the proposed configuration of the modular EV powertrain system has been developed. It combines the control of the operating modes with the functions of maintaining the required SOC level of the SCM and equalizing the SOCs of the two battery modules. The conducted simulation and experimental studies confirmed the workability and effectiveness of the proposed solutions.

Algorithm for controlling the movement of a multicopter as part of a group based on signals from the technical vision system

The paper analyzes the control of a group of multicopters during autonomous flight along an arbitrary trajectory determined by the leader. Under such a situation, the most acceptable option is the leader- follower model. Determining the relative location of the leader and the follower, as well as determining the parameters for controlling the movement of the follower, is proposed to be carried out using a technical vision system. For this, the leader is marked with a special label. A general flight control algorithm has been developed, which includes all its main stages from pre-flight preparation to landing. Controlling the movement of the follower is carried out by adjusting the angles of yaw, roll, pitch and changing the movement speed depending on the distance to the leader. The paper proposes formulas and algorithm for determining these parameters according to the system of technical vision and inertial navigation system of the follower. To test the proposed algorithms, a model was created in the Simulink software environment of the Matlab system. Experimental studies using a camera with a resolution of 1280x720 confirmed the correctness of the obtained ratios and algorithms. The maximum values of the error of full scale in determining the change in parameters for the distance, pitch and roll angles did not exceed 4%, and for the yaw angle - 6.1%. Increasing the accuracy of parameter determination is possible due to the use of a camera with a higher resolution.

An Evaluation of Propagation of the HIV-Infected Cells via Optimization Problem

Mathematical models have the potential to contribute to design and evaluate the infectivity spreading and growth of human immunodeficiency virus (HIV). Providing a better understanding of the dynamics of HIV infection in vivo and the immune system interactions with the virus can improve the classification of the infected cells and drive to an early diagnosis of the disease and drug evaluations. We analyze a two-dimensional environment HIV model from a new perspective, in terms of a multi-objective optimization problem, by introducing a linear modeling approach and providing numerical evidence for its suitability by introducing a general Instantaneous Control Algorithm.

Generalised adaptive optics method for high-NA aberration-free refocusing in refractive-index-mismatched media.

Phase aberrations are introduced when focusing by a high-numerical aperture (NA) objective lens into refractive-index-mismatched (RIM) media. The axial focus position in these media can be adjusted through either optical remote-focusing or mechanical stage translation. Despite the wide interest in remote-focusing, no generalised control algorithm using Zernike polynomials has been presented that performs independent remote-focusing and RIM correction in combination with mechanical stage translation. In this work, we thoroughly review derivations that model high-NA defocus and RIM aberration. We show through both numerical simulation and experimental results that optical remote-focusing using an adaptive device and mechanical stage translation are not optically equivalent processes, such that one cannot fully compensate for the other without additional aberration compensation. We further establish new orthogonal modes formulated using conventional Zernike modes and discuss its device programming to control high-NA remote-focusing and RIM correction as independent primary modes in combination with mechanical stage translation for aberration-free refocusing. Numerical simulations are performed, and control algorithms are validated experimentally by fabricating graphitic features in diamond using direct laser writing.

USVs‐Sim: A general simulation platform for unmanned surface vessels autonomous learning

AbstractUnmanned surface vessels (USVs) have been fully used in the civilian and military fields in recent years, which dramatically expands protective capability and detection range. However, the marine environment's complexity and variability make that verification of various advanced USVs control algorithms face high costs and high risks. In this article, we present USVs‐Sim, a novel high‐fidelity general simulation platform for USVs autonomous navigation data generation and control strategy testing. USVs‐Sim is a collection of high‐level extensible modules that allows the rapid development and testing of USVs configurations and facilitates the construction of complex ocean scenarios. USVs‐Sim supports the steering or thrusting limits of USVs, as well as unique dynamics profiles. The platform can specify specific USVs sensor systems and change the time of day and weather conditions to generate robust data. USVs‐Sim facilitates training of deep‐learning algorithms by enabling data export from USVs sensors, including vision data, lidar, relative positions of ocean targets. Therefore, USVs‐Sim allows for the rapid prototyping, development, and testing of USVs autonomous control algorithms in a complex marine environment. In this article, we detail the general simulation platform and testing several representative USVs intelligent control algorithms on the platform.

Generalized Control Algorithm and Artificial Intelligence Technology for Quadruped Walking Robot

Quadruped walking robot has superior adaptability and high adaptive mobility in various environments. These special advantages are particularly prominent in the mobile robot community. In this work, we introduce the omnidirectional gait and the rotational gait approach, which is a generalized control algorithm for executing any directional instruction. In addition, in order to improve the stability of the quadruped walking robot, we optimize the walking Angle and foot order. The proposed ideas were applied to the practical design of MRWallspect III, which was designed to examine large surfaces in industrial facilities. The effectiveness of the proposed method is verified by experiments on a robot.

Prioritize effluent quality, operational costs or global warming? – Using predictive control of wastewater aeration for flexible management of objectives in WRRFs

This study presents a general model predictive control (MPC) algorithm for optimizing wastewater aeration in Water Resource Recovery Facilities (WRRF) under different management objectives. The flexibility of the MPC is demonstrated by controlling a WRRF under four management objectives, aiming at minimizing: (A) effluent concentrations, (B) electricity consumption, (C) total operations costs (sum electricity costs and discharge effluent tax) or (D) global warming potential (direct and indirect nitrous oxide emissions, and indirect from electricity production) . The MPC is tested with data from the alternating WRRF in Nørre Snede (Denmark) and from the Danish electricity grid. Results showed how the four control objectives resulted in important differences in aeration patterns and in the concentration dynamics over a day. Controls B and C showed similarities when looking at total costs, while similarities in global warming potential for controls A and D suggest that improving effluent quality also reduced greenhouse gasses emissions. The MPC flexibility in handling different objectives is shown by using a combined objective function, optimizing both cost and greenhouse emissions. This shows the trade-off between the two objectives, enabling the calculation of marginal costs and thus allowing WRRF operators to carefully evaluate prioritization of management objectives. The long-term MPC performance is evaluated over 51 days covering seasonal and inter-weekly variations. On a daily basis, control A was 9–30% cheaper on average compared to controls A, D and to the current rule-based control. Similarly, control D resulted on average in 35–43% lower greenhouse gasses daily emission compared to the other controls. Difference between control performance increased for days with greater inter-diurnal variations in electricity price or greenhouse emissions from electricity production, i.e. when MPC has greater possibilities for exploiting input variations. The flexibility of the proposed MPC can easily accommodate for additional control objectives, allowing WRRF operators to quickly adapt the plant operation to new management objectives and to face new performance requirements.

Low voltage ride-through capability improvement of microgrid using a hybrid coordination control strategy

This paper proposes a hybrid coordination control strategy to improve the low voltage ride-through (LVRT) capability of microgrids. During microgrid external failure, the overcurrent and the voltage sag of the microgrid can be effectively suppressed. Compared with traditional control strategies, the microgrid transient performance can also be enhanced by adopting a generalized control algorithm, performing the active switching of the energy storage (ES) operation mode and triggering the inductance-type flux coupling fault current limiters (FCLs). Among them, according to the hierarchical control structure of the grid-connected inverter, the generalized control algorithm is applied to ES. Through the two degrees of freedom's control principle and inverse plant modeling techniques, the generalized control algorithm can make the control layer of the ES inverter operate in all control targets (i.e., PQ control, droop control and Vf control), with a single control structure. Also, it eliminates the effects of microgrid distortion voltage and ES surge current on the control system of the ES inverter. For the inverter application layer, by introducing microgrid voltage and angular frequency feedforward compensation, the voltage and frequency fluctuation of the microgrid can be suppressed efficiently under the fault conditions. Therefore, with the help of the generalized control algorithm, the active switching function of ES can be carried out successfully, which is the key technology for microgrids to realize their operational mode smooth switching. Meanwhile, the voltage sag and overcurrent of microgrids can be significantly mitigated through generating reactive power from microgrids and injecting it into inductance-type FCLs with lower cost. The related theoretical derivation and simulation analysis under various scenarios (including asymmetric faults) confirm that the proposed control strategy can not only enhance the LVRT capability, but also strengthen the microgrid transient performance.

Dual <inline-formula> <tex-math notation="LaTeX">$P$</tex-math> </inline-formula>-<inline-formula> <tex-math notation="LaTeX">$Q$</tex-math> </inline-formula> Theory Based Energy-Optimized Dynamic Voltage Restorer for Power Quality Improvement in a Distribution System

This paper deals with the protection of critical loads from voltage-related power quality issues using a dynamic voltage restorer (DVR). A generalized control algorithm based on instantaneous space phasor and dual $P$ - $Q$ theory has been proposed to generate the instantaneous reference voltages to compensate the load voltages with direct power flow control. The proposed algorithm adapts energy-optimized series voltage compensation, which results in a reduction of energy storage requirement. The proposed DVR control scheme can support the load from voltage-related power quality issues irrespective of the load current profile. Each leg of the three-phase three-leg split capacitor inverter is used to inject series compensation voltage in respective phases of the system. Model-based computer simulation studies and real-time experimental results validate the effectiveness of the proposed control algorithm.

A Stationary-Frame Current Vector Control Strategy for Single-Phase PWM Rectifier

Traditional current control methods for a single-phase rectifier in an electric traction drive system suffer from either long response time or nonzero steady-state error. A novel current vector control strategy in stationary-frame is therefore proposed, in this paper, to improve the control performance of a rectifier. The mathematic model of the single-phase two-level pulse rectifier was first analyzed by complex space vector. Then, the principle of the proposed current control method was described. Based on this, the implementation and parameter tuning method of the current control algorithm based on a space complex vector in a two-phase stationary coordinate system are presented. Moreover, two kinds of general current control algorithms are analyzed and compared with the proposed algorithm to demonstrate the advantages of the proposed algorithm. The proposed control scheme absorbs advantages of the conventional control schemes, including fast response, zero steady-state error, and active and reactive power independent control, but overcomes their shortcomings. Finally, the theoretical analysis is verified by means of simulation as well as a hardware-in-loop experimental test on an experimental laboratory setup and some comparisons with conventional current control algorithms prove the advantages of the utilized method.

A numerical algorithm for group control of conventional/unconventional production wells in hydrocarbon reservoirs

PurposeThe purpose of this paper is to present detailed algorithms for simulation of individual and group control of production wells in hydrocarbon reservoirs which are implemented in a finite volume-based reservoir simulator.Design/methodology/approachThe algorithm for individual control is described for the multi-lateral multi-connection ones based on the multi-segment model considering cross-flow. Moreover, a general group control algorithm is proposed which can be coupled with any well model that can handle a constraint and returns the flow rates. The performance of oil production process based on the group control criteria is investigated and compared for various cases.FindingsThe proposed algorithm for group control of production wells is a non-optimization iterative scheme converging within a few number of iterations. The numerical results of many computer runs indicate that the nominal power of the production wells, in general, is the best group control criterion for the proposed algorithm. The production well group control with a proper criterion can generally improve the oil recovery process at negligible computational costs when compared with individual control of production wells.Research/limitations/implicationsAlthough the group control algorithm is implemented for both production and injection wells in the developed simulator, the numerical algorithm is here described only for production wells to provide more details.Practical/implicationsThe proposed algorithm can be coupled with any well model providing the fluid flow rates and can be efficiently used for group control of production wells. In addition, the calculated flow rates of the production wells based on the group control algorithm can be used as candidate solutions for the optimizer in the simulation-optimization models. It may reduce the total number of iterations and consequently the computational cost of the simulation-optimization models for the well control problem.Originality/valueA complete and detailed description of ingredients of an efficient well group control algorithm for the hydrocarbon reservoir is presented. Five group control criteria are extracted from the physical, geometrical and operating conditions of the wells/reservoir. These are the target rate, weighted potential, ultimate rate and introduced nominal power of the production wells. The performance of the group control of production wells with different group control criteria is compared in three different oil production scenarios from a black-oil and highly heterogeneous reservoir.

General contact force control algorithm in double-sided incremental forming

The utilization of a supporting tool in Double-Sided Incremental Forming (DSIF) imposes a stabilizing compressive stress through the sheet’s thickness, increasing, thereby, the material’s formability and fatigue life. However, these favorable effects strongly depend on a steady tool-metal contact condition. This work presents a general DSIF control scheme, which augments the conventional position servo-loop with explicit force feedback control. The algorithm is examined for its robustness and effectiveness using complex geometries with varying curvatures and wall angles. The resulting parts have demonstrated enhanced material formability and geometric accuracy.

How to achieve precise operation of a robotic manipulator on a macro to micro/nano scale

PurposeThe purpose of this paper is to present state-of-the-art approaches for precise operation of a robotic manipulator on a macro- to micro/nanoscale.Design/methodology/approachThis paper first briefly discussed fundamental issues associated with precise operation of a robotic manipulator on a macro- to micro/nanoscale. Second, this paper described and compared the characteristics of basic components (i.e. mechanical parts, actuators, sensors and control algorithm) of the robotic manipulator. Specifically, commonly used mechanisms of the manipulator were classified and analyzed. In addition, intuitive meaning and applications of its actuator explained and compared in details. Moreover, related research studies on general control algorithm and visual control that are used in a robotic manipulator to achieve precise operation have also been discussed.FindingsRemarkable achievements in dexterous mechanical design, excellent actuators, accurate perception, optimized control algorithms, etc., have been made in precise operations of a robotic manipulator. Precise operation is critical for dealing with objects which need to be manufactured, modified and assembled. The operational accuracy is directly affected by the performance of mechanical design, actuators, sensors and control algorithms. Therefore, this paper provides a categorization showing the fundamental concepts and applications of these characteristics.Originality/valueThis paper presents a categorization of the mechanical design, actuators, sensors and control algorithms of robotic manipulators in the macro- to micro/nanofield for precise operation.

An equivalent continuum multiscale formulation for 2D geometrical nonlinear analysis of lattice truss structure

In this work, an equivalent continuum multiscale formulation is presented for the geometrical nonlinear analysis of the structures with lattice truss materials. This formulation is established by combining the extended multiscale finite element method and the co-rotational approach. Firstly, the lattice truss unit cell is equivalent to a continuum coarse element by using a numerical constructed interpolation function in the local coordinate system. Then the tangent stiffness matrix of this coarse element is derived by employing the basic idea of the co-rotational approach in the global coordinate system. Thus, the global nonlinear equilibrium equations of the structure at the macroscopic level can be solved by using the general displacement control algorithm to capture the equilibrium path with multiple critical points. After performing all of the incremental steps and the iterative steps on the macroscopic scale, the microscopic information, such as the displacement, stress and strain, can be obtained easily by virtue of the afore-constructed numerical interpolation functions once again. In addition, several numerical examples are carried out to study the effects of the layout and size of unit cell, investigate the sensitivity of coarse-scale meshes and verify the validation and efficiency of the presented multiscale formulation.

Constraint-Based and Sensorless Force Control With an Application to a Lightweight Dual-Arm Robot

The increasing demand for flexible robotized solutions in SMEs motivates the research on innovative and general control algorithms suitable for a large variety of applications. Particularly suited for this are constraint-based trajectory generation and control methods, which have been deeply investigated in the last decade. In this letter, we present an application of such a control framework for sensorless execution of a force control task as applied to a dual-arm redundant manipulator. Experiments and simulations confirm the effectiveness of the approach, even in the case of parametric uncertainties.

Design of a Generalized Control Algorithm for Parallel Inverters for Smooth Microgrid Transition Operation

A modified hierarchical control structure for distributed generation (DG) in microgrid is applied in accordance to the recommendations by the IEEE Std. 1676. In the inverter control layer, a generalized control algorithm is developed to enable the DGs to operate in all three modes (i.e., grid-forming, grid-feeding, and grid-supporting modes) with a single control structure, facilitating the seamless transition between the operating modes. This feature is obtained by designing the multiloop controller in the inverter control layer using inverse plant modeling techniques so that the dynamics of the inverter and the $LC$ filter are fully compensated, virtually transforming the controlled DG in the unity gain from the application layer perspective. Thus, effects of disturbances associated with the mode transitions are thus fully eliminated. The effectiveness of the proposed control algorithm is validated by numerical simulations and hardware-in-the-loop experiments. The results show that the DGs can fulfill the tasks defined in the system control layer with fast dynamics, desired accuracy, and good transient behavior.

An inverse-model approach to multivariable norm optimal iterative learning control with auxiliary optimisation

Motivated by the commonly encountered problem in which tracking is only required at selected intermediate points within the time interval, a general optimisation-based iterative learning control (ILC) algorithm is derived that ensures convergence of tracking errors to zero whilst simultaneously minimising a specified quadratic objective function of the input signals and chosen auxiliary (state) variables. In practice, the proposed solutions enable a repeated tracking task to be accurately completed whilst simultaneously reducing undesirable effects such as payload spillage, vibration tendencies and actuator wear. The theory is developed using the well-known norm optimal ILC (NOILC) framework, using general linear, functional operators between real Hilbert spaces. Solutions are derived using feedforward action, convergence is proved and robustness bounds are presented using both norm bounds and positivity conditions. Algorithms are specified for both continuous and discrete-time state-space representations, with the latter including application to multi-rate sampled systems. Experimental results using a robotic manipulator confirm the practical utility of the algorithms and the closeness with which observed results match theoretical predictions.

The Control Algorithm Research of Yarn Tension for Winding Machine Based on Grey Prediction Model

For building high precision yarn tension control model, grey prediction method was first employed in this paper. The commonly used GM(1,1) model was modified by means of changing the coefficient a and b. Then the next tension value was forecasted from the previous test values by the modified GM(1,1) model. Then the forecasted values and the referred value were import into the self-adaption PID model. And the PID model output the control sign to magnetic particle clutch. The simulation of the control algorithm was completed in MATLAB 7.0. The simulation result showed that the proposed control algorithm had better precision than general PID and general grey prediction control algorithm.