Real-time Control Algorithm Research Articles

A Real-Time Combustion Control With Reconstructed In-Cylinder Pressure by Principal Component Analysis for a CRDI Diesel Engine

This paper proposes a real-time combustion control algorithm using reconstructed in-cylinder pressure traces by principal component analysis (PCA). The PCA method reconstructs the in-cylinder pressure traces using the principal components of the in-cylinder pressure traces. It was shown that using only five principal components, we were able to reconstruct the in-cylinder pressure traces within 1% root mean squared percent error. Furthermore, the reconstructed in-cylinder pressure traces were validated to effectively reduce the cycle-to-cycle variations caused by the noise signals. As a result, the standard deviation of MFB50 which was calculated from the reconstructed in-cylinder pressure was reduced by 45%. Furthermore, this combustion parameter was applied to a real-time combustion control. Since variations of the control variables for the real-time combustion control were reduced, the control performances were enhanced.

Development and Implementation of Control Algorithms for Synchronous Generator

This paper proposes a DSP based simulator for development and implementation of control algorithms. The simulator is used to control a synchronous aggregate model in real time. The simulator consists of a PC (on which a synchronous generator connected to AC network is simulated) connected through a communication channel to a DSP (on which the control algorithm is implemented). The simulator makes implementation of a control algorithm faster and easier. It also enables verification of a control algorithm in real time. Simulation results show that there are no significant differences between non-real time simulations (on a PC) and real time simulations (on a DSP based simulator). This paper also presents design and implementation of a nonlinear control algorithm for excitation control system based on the Lyapunov's direct method. Both conventional excitation control algorithm and proposed nonlinear excitation control algorithm were implemented and tested on the real time simulator. The obtained simulation results show that proposed nonlinear excitation control algorithm better damps electromechanical oscillations than conventional excitation control algorithm.

(Invited) Analyzing and Minimizing Capacity Fade through Optimal Model-based Control - Theory and Experimental Validation

In order to significantly expand the BEV market, and to increase the use of lithium-ion batteries in electric grids, there is a need to develop optimal charging strategies to utilize the batteries more efficiently and enable longer life. Advanced battery management systems that can calculate and implement such strategies in real time are expected to play a critical role for this purpose. This article investigates different approaches for determining model-based optimal charging profiles for batteries, and experimentally validates the gain obtained using such profiles. Optimal profiles that maximize the cycle life of the cells are implemented on 16 Ah NMC cells for 30 minutes of charge followed by 5C discharge, and the cycle life is compared to a standard 2C CC-CV charge and 5C discharge. An improvement of more than 100% in cycle life is observed experimentally, for our test conditions on this cell design. This study is the first to experimentally demonstrate that the improved extra knowledge obtained by sophisticated physics-based models results in significant improvements in battery performance when employed in a real time control algorithm.

Time-domain versus frequency-domain effort weighting in active noise control design

Active noise control is often designed by minimizing an error index which includes a penalty on the actuator inputs. In this way, an effort-weighting parameter allows one to monitor the maximum voltages applied to the control sources. Two effort-weighting techniques have been widely implemented in previous studies, Tikhonov regularization for frequency-domain simulations and the leaky filtered-reference least mean square algorithm for real-time feedforward control. This paper introduces the formal connection between the weighting parameters of these two techniques. Simulations of a simple set-up show that, with these two connected parameters, the control performances are indeed very close.

부유분진측정기(PM10) 관측 자료 실시간 품질관리 알고리즘 개발 및 평가

A real-time quality control algorithm for <TEX>$PM_{10}$</TEX> concentration measured by Continuous Ambient Particulate Monitor (FH62C14, Thermo Fisher Scientific Inc.) has been developed. The quality control algorithm for <TEX>$PM_{10}$</TEX> data consists of five main procedures. The first step is valid value check. The values should be within the acceptable range limit. Upper (<TEX>$5,000{\mu}g\;m^{-3}$</TEX>) and lower (<TEX>$0{\mu}g\;m^{-3}$</TEX>) values of instrument detectable limit have to be eliminated as being unrealistic. The second step is valid error check. Whenever unusual condition occurs, the instrument will save error code. Value having an error code is eliminated. The third step is persistence check. This step checks on a minimum required variability of data during a certain period. If the <TEX>$PM_{10}$</TEX> data do not vary over the past 60 minutes by more than the specific limit (<TEX>$0{\mu}g\;m^{-3}$</TEX>) then the current 5-minute value fails the check. The fourth step is time continuity check, which is checked to eliminate gross outlier. The last step is spike check. The spikes in the time series are checked. The outlier detection is based on the double-difference time series, using the median. Flags indicating normal and abnormal are added to the raw data after quality control procedure. The quality control algorithm is applied to <TEX>$PM_{10}$</TEX> data for Asian dust and non-Asian dust case at Seoul site and dataset for the period 2013~2014 at 26 sites in Korea.

Real-time myoelectric control for a lower-limb assistive exoskeleton

This paper describes the approach to a novel algorithm for real-time myoelectric onset detection based on the classic moving average method with added features to provide onset detection while myoelectric signals are recorded from two muscles at a time. The aim of this algorithm is focused on the generation of real-time binary signals to drive a dc motor attached to the hip joint of a rehabilitation exoskeleton for the assistance on lower-limb rehabilitation of hemiplegic patients in supine/prone, seated and standing positions. With this low computational cost real-time control algorithm based on myoelectric signals, patients involved on a physical rehabilitation program wearing the developed exoskeleton will have full control over the assistance for the lower-limb exercises. The parameter tuning for the myoelectric onset detection algorithm and the results of its accuracy along several tests over two test subjects on the rectus femoris and semitendinosus muscles are presented.

Multi-objective energy management optimization and parameter sizing for proton exchange membrane hybrid fuel cell vehicles

The powertrain system of a typical proton electrolyte membrane hybrid fuel cell vehicle contains a lithium battery package and a fuel cell stack. A multi-objective optimization for this powertrain system of a passenger car, taking account of fuel economy and system durability, is discussed in this paper. Based on an analysis of the optimum results obtained by dynamic programming, a soft-run strategy was proposed for real-time and multi-objective control algorithm design. The soft-run strategy was optimized by taking lithium battery size into consideration, and implemented using two real-time algorithms. When compared with the optimized dynamic programming results, the power demand-based control method proved more suitable for powertrain systems equipped with larger capacity batteries, while the state of charge based control method proved superior in other cases. On this basis, the life cycle cost was optimized by considering both lithium battery size and equivalent hydrogen consumption. The battery capacity selection proved more flexible, when powertrain systems are equipped with larger capacity batteries. Finally, the algorithm has been validated in a fuel cell city bus. It gets a good balance of fuel economy and system durability in a three months demonstration operation.

통행시간과 점유율 기반의 실시간 신호운영 알고리즘

본 연구에서는 통행시간과 점유율의 융합 정보를 이용하는 새로운 실시간 신호제어 알고리즘을 제시하였다. 교통정보시스템의 통행시간 정보를 신호운영에 적용하였으며, 통행시간으로 부터 산정한 포화도를 신호제어에 이용하기 위한 프로세스를 개발하였다. 결정적 지체모형을 이용해 통행시간으로부터 대기행렬 길이를 생성하고, 대기행렬 길이를 다시 포화도로 변환하는 과정이 적용되었다. 또한 통행시간 기반 포화도와 루프검지기 포화도를 융합해 신호시간이 산정되도록 하였다. 신호제어 알고리즘의 효과평가를 위해 미시적 시뮬레이션 분석을 시행하였으며, 과포화 상태에서 기존 루프검지기 기반 실시간 신호제어 대비 최대 27%의 지체 감소 효과를 확인하였다. 또한 과포화 및 검지기 고장상황에 대한 효과적이고, 유용한 대응이 가능함을 확인하였다. 본 연구에서는 교통신호제어시스템과 교통정보시스템의 교통정보 통합이용 방안을 제시하였다는데 의의가 있겠다. This research suggested a new real-time traffic signal control algorithm using fusion data of the travel time and the occupancy rate. This research applied the travel time data of traffic information system to traffic signal operation, and developed the signal control process using the degree of saturation that was estimated from the travel time data. This algorithm estimates a queue length from the travel time based on a deterministic delay model, and includes the process to change from the queue length to the degree of saturation. In addition, this model can calculate the traffic signal timings using fusion data of the travel time and the occupancy rate based on the saturation degree. The micro simulation analysis was conducted for effectiveness evaluation. We checked that the average delay decreased by up to 27 percent. In addition, we checked that this signal control algorithm could respond to a traffic condition of oversaturation and detector breakdown effectively and usefully. This research has important contribution to apply the traffic information system to traffic signal operation sectors.

Seismic damage control of nonlinear continuous reinforced concrete bridges under extreme earthquakes using MR dampers

Under extreme earthquakes, a continuous bridge tends to fail because of the damage to the bearing or the pier. A strong connection between the girder and the pier decreases the bearing displacement, but the increased inertia force of the girder to the base of the pier leads to pier damage. Conversely, a weak connection while protecting the pier causes bearing damage. In many cases, the bridge loses its function due to the damages concentrated on local members, while the rest of the members remain undamaged. To simultaneously protect both the bearing and pier during earthquakes with an evenly distributed damage pattern, a new real-time semi-active control algorithm based on the damage of bridge members (RTSD) using magneto-rheological (MR) dampers is proposed. Two displacement indices are established to represent the damage status of the bearing and pier and are used as control signals for the MR damper forces. A typical three-span continuous reinforced concrete bridge modeled by nonlinear fiber damage elements is used for the demonstration of the proposed method. Passive controls using viscous dampers (PVD) and MR dampers with a constant current (PMR) are also adopted for comparisons. Numerical simulation results show that the proposed method is more effective in protecting the bearing and pier than the passive controls. With the RTSD control, the damages to the bearing and pier are balanced and the limited damages to each pier can be evenly developed within the allowable range. Moreover, the initial damper force can be set in a wide range for the RTSD control to protect both the bearing and pier under various earthquakes. In contrast, it is impossible to select a proper damper force by passive controls. The RTSD control can also control the pier damage within different prescribed targets under extreme earthquakes.

Real-Time Nonlinear Model Predictive Control of a Transport–Reaction System

Two real-time nonlinear model predictive control (NMPC) algorithms for a transport–reaction system are designed. The system is modeled by a hyperbolic partial differential equation and discretized by means of a two-time-level semi-implicit semi-Lagrangian scheme. For the resulting lumped-parameter system, a constrained optimal control problem is formulated and state constraints are implemented in the form of barrier functions. The NMPC algorithms perform a single step or several steps of an iterative solution routine of the optimal control problem at every sampling point. With this suboptimal solution strategy, a fixed maximum evaluation time and execution in real time are guaranteed. An analysis of the nominal stability is provided for one NMPC scheme. The robustness of the controllers is evaluated for an example problem, where a nonisothermal plug-flow reactor with irreversible exothermic reactions is considered. The control objectives are to limit the maximum reactor temperature (avoid hot spots) and to maximize the process output.

Study of vibration control using laboratory test rig of wind turbine tower-nacelle system with MR damper based tuned vibration absorber

Abstract Wind turbine tower dynamic stress is related to the fatigue wear and reliability of the whole wind turbine structure. This paper deals with the problem of tower vibration control using a specially designed and built laboratory model. The considered wind turbine tower-nacelle model consists of a vertically arranged stiff rod (representing the tower), and a system of steel plates (representing nacelle and turbine assemblies) fixed at its top. The horizontally aligned tuned vibration absorber (TVA) with magnetorheological (MR) damper is located also at the top of the rod (in nacelle system). Force excitation sources applied horizontally to the tower itself and to the nacelle were both considered. The MR damper real-time control algorithms, including ground hook control and its modification, sliding mode control, linear and nonlinear (cubic and square root) damping, and adaptive solutions are compared to the open-loop case with various constant MR damper input current values and system without MR TVA (i.e., MR TVA in “locked” state). Comprehensive experimental analyses and their results are presented.

Decentralized Control of Oscillatory Dynamics in Power Systems Using an Extended LQR

This paper proposes a decentralized algorithm for real-time control of oscillatory dynamics in power systems. The algorithm integrates dynamic state estimation (DSE) with an extended linear quadratic regulator (ELQR) for optimal control. The control for one generation unit only requires measurements and parameters for that unit, and hence the control at a unit remains completely independent of other units. The control gains are updated in real-time, therefore the control scheme remains valid for any operating condition. The applicability of the proposed algorithm has been demonstrated on a representative power system model.

수직다관절형 아암의 운동학적 모델링 및 관절공간 모션제어에 관한 연구

In this paper, we propose a new technique to the design and real-time control of an adaptive controller for robotic manipulator based on digital signal processors. The Texas Instruments DSPs(TMS320C80) chips are used in implementing real-time adaptive control algorithms to provide enhanced motion control performance for dual-arm robotic manipulators. In the proposed scheme, adaptation laws are derived from model reference adaptive control principle based on the improved Lyapunov second method. The proposed adaptive controller consists of an adaptive feed-forward and feedback controller and time-varying auxiliary controller elements. The proposed control scheme is simple in structure, fast in computation, and suitable for real-time control. Moreover, this scheme does not require any accurate dynamic modeling, nor values of manipulator parameters and payload. Performance of the proposed adaptive controller is illustrated by simulation and experimental results for a dual arm robot manipulator with eight joints. joint space and cartesian space.

An integrodifferential approach to modeling, control, state estimation and optimization for heat transfer systems

Abstract In this paper, control-oriented modeling approaches are presented for distributed parameter systems. These systems, which are in the focus of this contribution, are assumed to be described by suitable partial differential equations. They arise naturally during the modeling of dynamic heat transfer processes. The presented approaches aim at developing finite-dimensional system descriptions for the design of various open-loop, closed-loop, and optimal control strategies as well as state, disturbance, and parameter estimation techniques. Here, the modeling is based on the method of integrodifferential relations, which can be employed to determine accurate, finite-dimensional sets of state equations by using projection techniques. These lead to a finite element representation of the distributed parameter system. Where applicable, these finite element models are combined with finite volume representations to describe storage variables that are—with good accuracy—homogeneous over sufficiently large space domains. The advantage of this combination is keeping the computational complexity as low as possible. Under these prerequisites, real-time applicable control algorithms are derived and validated via simulation and experiment for a laboratory-scale heat transfer system at the Chair of Mechatronics at the University of Rostock. This benchmark system consists of a metallic rod that is equipped with a finite number of Peltier elements which are used either as distributed control inputs, allowing active cooling and heating, or as spatially distributed disturbance inputs.

In-cylinder pressure based real-time combustion control for reduction of combustion dispersions in light-duty diesel engines

This paper proposes an in-cylinder pressure based real-time combustion control algorithm to reduce combustion dispersions from diesel engines. The proposed algorithm manipulates main injection quantity and timing as well as pilot injection quantity to control the Indicated Mean Effective Pressure (IMEP), crank angle location where 50% of Mass Fraction Burned (MFB50) and maximum value of Rate of Heat Release (ROHRmax). This control algorithm reduces the combustion dispersions by controlling the heat release curve for each operating condition.The proposed real-time combustion control structure mitigates combustion dispersions caused by operating condition changes, un-calibrated fuel injectors, and environmental condition variations, and it is validated with various experiments. In these experiments, various engine control variables were changed to validate the reduction in combustion dispersion when operating conditions change unintendedly. Changes in coolant temperature verified the compensation effect of the proposed algorithm under different external environments. It is validated with these experiments that there are 30% reduction in torque imbalances, a 10% emission dispersions reduction for NOx emissions, and a 65% reduction for PM emissions.

Dynamic Stiffness Analysis of Repetitive Control System

For dynamic stiffness enhancement, this paper presents a new method for synthesizing repetitive controllers capable of rejecting periodic vibration disturbance. Dynamic stiffness of the control system is analyzed. Direct and quadrature dynamic stiffness are defined for the repetitive controllers’ design. A trade-off method between the determinations of the controller’s parameters is necessary such that both the rejecting performance and stability can be achieved simultaneously. An illustrated example of a twin linear drive system is given to verify the performance of the proposed control design. The control performance of the present method is evaluated in the experimental disturbance rejecting control system, where the real-time control algorithms are implemented using a floating-point digital signal processor. Both computer simulation and experimental results are presented to illustrate the effectiveness of the proposed repetitive controller design.

Real-Time power control algorithm for reactive power reserve of Wind Farm

Abstract: Reactive power assignment has not been considered seriously in wind power because many system owners manage real power output firstly and maintain the required voltage for each wind turbine. However, renewable resources penetration is being continuously increased and power system operator might ask additional service to improve the reliability and stability issues. Owing to the system loss by the extensive area, the uncertainty of transferred power from large-scale wind farm is considerable. Counterbalancing the gap between expected and real output quantity is available with additional control design but reducing the occurred error is more effectual to not only the system efficiency but also the system stability. In this paper, a reactive power assignment strategy based on the relative distance of each wind turbine in farm, and realistic assignment processes to verify the positive effect are performed by PSCAD/EMTDC. The strategy is considering voltage fluctuation and system loss by two distinguished assignment processes that regarding array and turbines.

An Improved Adaptive Signal Control Method for Isolated Signalized Intersection Based on Dynamic Programming

The performance of an adaptive signal control system largely depends on the embedded traffic flow prediction and control algorithm. This paper proposes an improved adaptive control method, comprised of a vehicle arrival estimation model and a signal optimization algorithm. Firstly, a microscopic model was developed to capture vehicle arrival dynamics both in red and green durations. Based on the upstream detection information, vehicle arrival time is predicted taking account of signal timing, vehicle trajectory and variable queue length. The real-time signal control algorithm was formulated based on a Dynamic Programming (DP) procedure, supporting NEMA phase configuration. Three objective functions were considered respectively, namely minimization of delay, queue length and maximization of throughput. The proposed adaptive control method was implemented in VISSIM on a real signalized intersection. It is shown that DP with NEMA generally outperforms DP with 4-phase and the signal timings generated by SYNCHRO. Different objective functions lead to different control performance in terms of various demands and planning horizons. It is reasonably believed that the model has potential applicability in real time traffic adaptive signal control systems.

Real-Time Distributed Control of Battery Energy Storage Systems for Security Constrained DC-OPF

The introduction of fast-response battery energy storage system (BESS) provides a number of advantages to address the new challenges of smart grids, including improving the reliability and security of the power grids. This paper proposes a real-time distributed control algorithm to the corrective security-constrained DC optimal power flow problem for transmission network. The objective is to minimize the adjustment of the BESSs, while maintaining the supply-demand balance and ensuring no security constraint violations in the post-contingency state for the short-term period. Comparing to the conventional centralized methods, only simple local computation and information exchange with neighbors are required to update the local control signal, which leads to fast response of the BESSs to alleviate the impact of the transmission line outage. Real-time simulation results of the modified 6-bus and 24-bus systems demonstrate that the dynamic performances of proposed distributed algorithm satisfy standard requirements and indicate its applicability for practical power grid.

Real-Time Merging Traffic Control at Congested Freeway Off-Ramp Areas

This study presents a real-time merging traffic control algorithm to mitigate the problem of freeway congestion resulting from an overspilling off-ramp. The proposed control algorithm aims at maximizing the merge area outflow of the surface street and at the same time preventing the off-ramp queue spillover into the freeway mainstream and the resulting freeway congestion. The potential benefits obtained by applying the proposed control concept are demonstrated by the use of microscopic simulation applied to a real freeway network where recurrent freeway traffic congestion is created as a result of an overspilling off-ramp. The simulation results demonstrated that the proposed control algorithm may improve the prevailing traffic conditions, preventing the formation of freeway congestion and benefiting freeway drivers and surface street users.