矿用机械设备正流量液压系统电控算法应用

随着科技的发展,矿用机械设备也在日益更新,使得矿场工作效率日益提升,真正发挥了正流量液压系统的作用。在此过程中,不仅要了解正流量液压系统的基本组成,也要了解其工作原理,掌握其电控算法,才能有效控制矿用机械设备,进而促使矿场正常运转。本篇文章主要介绍矿用机械设备正流量液压系统的基本组成、工作原理以及其电控算法,旨在提供参考。

Combining Market-Based Control with Distribution Grid Constraints when Coordinating Electric Vehicle Charging

The charging of electric vehicles(EVs) impacts the distribution grid, and its cost depends on the price of electricity when charging. An aggregator that is responsible for a large fleet of EVs can use a market-based control algorithm to coordinate the charging of these vehicles, in order to minimize the costs. In such an optimization, the operational parameters of the distribution grid, to which the EVs are connected, are not considered. This can lead to violations of the technical constraints of the grid(e.g., undervoltage, phase unbalances); for example, because many vehicles start charging simultaneously when the price is low. An optimization that simultaneously takes the economic and technical aspects into account is complex, because it has to combine time-driven control at the market level with eventdriven control at the operational level. Diff erent case studies investigate under which circumstances the market-based control, which coordinates EV charging, conflicts with the operational constraints of the distribution grid. Especially in weak grids, phase unbalance and voltage issues arise with a high share of EVs. A low-level voltage droop controller at the charging point of the EV can be used to avoid many grid constraint violations, by reducing the charge power if the local voltage is too low. While this action implies a deviation from the cost-optimal operating point, it is shown that this has a very limited impact on the business case of an aggregator, and is able to comply with the technical distribution grid constraints, even in weak distribution grids with many EVs.

Elevator Group-Control Policy Based on Neural Network Optimized by Genetic Algorithm

Aiming at the diversity and nonlinearity of the elevator system control target, an effective group method based on a hybrid algorithm of genetic algorithm and neural network is presented in this paper. The genetic algorithm is used to search the weight of the neural network. At the same time, the multi-objective-based evaluation function is adopted, in which there are three main indicators including the passenger waiting time, car passengers number and the number of stops. Different weights are given to meet the actual needs. The optimal values of the evaluation function are obtained, and the optimal dispatch control of the elevator group control system based on neural network is realized. By analyzing the running of the elevator group control system, all the processes and steps are presented. The validity of the hybrid algorithm is verified by the dynamic imitation performance.

Neural adaptive PSD decoupling controller and its application in three-phase electrode adjusting system of submerged arc furnace

Taking three-phase electrode adjusting system of submerged arc furnace as study object which has nonlinear, time-variant, multivariable and strong coupling features, a neural adaptive PSD(proportion, sum and differential) dispersive decoupling controller was developed by combining neural adaptive PSD algorithm with dispersive decoupling network. In this work, the production technology process and control difficulties of submerged arc furnace were simply introduced, the necessity of establishing a neural adaptive PSD dispersive decoupling controller was discussed, the design method and the implementation steps of the controller are expounded in detail, and the block diagram of the controlled system is presented. By comparison with experimental results of the conventional PID controller and the adaptive PSD controller, the decoupling ability, adaptive ability, self-learning ability and robustness of the neural adaptive PSD dispersive decoupling controller have been testified effectively. The controller is applicable to the three-phase electrode adjusting system of submerged arc furnace, and it will play an important role for achieving the power balance of three-phrase electrodes, saving energy and reducing consumption in the process of smelting.

Genetic algorithm tuned PI controller on PMSM simplified vector control

A simple control structure in servo system is occasionally needed for simple industrial application which precise and high control performance is not exessively important so that the cost production can be reduced efficiently. Simplified vector control, which has simple control structure, is utilized as the permanent magnet synchronous motor control algorithm and genetic algorithm is used to tune three PI controllers used in simplified vector control. The control performance is obtained from simulation and investigated to verify the feasibility of the algorithm to be applied in the real application. Simulation results show that the speed and torque responses of the system in both continuous time and discrete time can achieve good performances. Furthermore, simplified vector control combined with genetic algorithm has a similar perfofmance with conventional field oriented control algorithm and possible to be realized into the real simple application in the future.

Optimal coordinated voltage control of power systems

An immune algorithm solution is proposed in this paper to deal with the problem of optimal coordination of local physically based controllers in order to preserve or retain mid and long term voltage stability. This problem is in fact a global coordination control problem which involves not only sequencing and timing different control devices but also tuning the parameters of controllers. A multi-stage coordinated control scheme is presented, aiming at retaining good voltage levels with minimal control efforts and costs after severe disturbances in power systems. A self-pattem-recognized vaccination procedure is developed to transfer effective heuristic information into the new generation of solution candidates to speed up the convergence of the search procedure to global optima. An example of four bus power system case study is investigated to show the effectiveness and efficiency of the proposed algorithm, compared with several existing approaches such as differential dynamic programming and tree-search.

Research of the test generation algorithm based on search state dominance for combinational circuit

On the basis of EST (Equivalent STate hashing) algorithm, this paper researches a kind of test generation algorithm based on search state dominance for combinational circuit. According to the dominance relation of the E-frontier (evaluation frontier), we can prove that this algorithm can terminate unnecessary searching step of test pattern earlier than the EST algorithm through some examples, so this algorithm can reduce the time of test generation. The test patterns calculated can detect faults given through simulation.

Study on simulation and scheduling algorithm of CAN control for independently driving electric vehicle

Safety-critical applications such as the independently driving systems of electric vehicle （EV） require a high degree of reliability. The controller area network （CAN） is used extensively in the control sectors. A new real-time and reliable scheduling algorithm based on time-triggered scheduler with a focus on the CAN-based distributed control systems for independently driving EV is exploited. A distributed control network model for a dual-wheel independendy driving EV is established. The timing and reliabili- ty analysis in the worst case with the algorithm is used to evaluate the predictability and dependability and the simulation based on the algorithm with CANoe software is designed. The results indicate the algorithm is more predicable and dependable.

New Intellectual Economized Technique on Electricity Based on DSP

In order to resolve the problean of the unbalanced threephase and unstable voltage, intellectual economized technique on elec- tricity based on electromagnetic regulation and control is proposed in this paper. We choose the TMS320LF2407A as the control chip and stepper motor as the executing agency. The equipment controls the movable contact reaching to the assigned position on the magnetic coil quickly and accurately, and outputs the sine-wave voltage steadily along with the network voltage variation though the fuzzy Porportional Integral Derivative（PID） control algorithm of integral separation and incremental mode with setting dead area. The principle of work and the key technique on the electromagnetic regulation and control are introduced in detail in this paper. The experiment result gives a proof for all the algorithm mentioned in this paper.

FULMS algorithm based multi channel active vibration control of piezoelectric flexible beam

A multi-channel active vibration controller based on a filtered-u least mean square （FULMS） control algorithm is analyzed and implemented to solve the problem that the vibration feedback may affect the measuring of the reference signal of the filtered-x least mean square （FXLMS） algorithm in the field of active vibration control. By analyzing the multi-channel FULMS algorithm, the multi-channel controller structure diagram is given, while by analyzing multi-channel FXLMS algorithm and its algorithmic procedure, the control channel model identification strategy is given. This paper also provides an easy but practical way to configure the actuators based on the maximal modal force rule. Taking the configured piezoelectric beam as the research object, an active vibration control experimental platform is established to verify the effectiveness of the identification strategy as well as the FULMS control scheme. Simulation and actual control experiments are done after the model parameters are obtained. Both the simulation and actual experiment results show that the designed multi-channel vibration controller has a good control performance with low order model and rapid convergence.

Control allocation algorithm for over-actuated electric vehicles

A control allocation algorithm based on pseudo-inverse method was proposed for the over-actuated system of four in-wheel motors independently driving and four-wheel steering-by-wire electric vehicles in order to improve the vehicle stability. The control algorithm was developed using a two-degree-of-freedom(DOF) vehicle model. A pseudo control vector was calculated by a sliding mode controller to minimize the difference between the desired and actual vehicle motions. A pseudo-inverse controller then allocated the control inputs which included driving torques and steering angles of the four wheels according to the pseudo control vector. If one or more actuators were saturated or in a failure state, the control inputs are re-allocated by the algorithm. The algorithm was evaluated in Matlab/Simulink by using an 8-DOF nonlinear vehicle model. Simulations of sinusoidal input maneuver and double lane change maneuver were executed and the results were compared with those for a sliding mode control. The simulation results show that the vehicle controlled by the control allocation algorithm has better stability and trajectory-tracking performance than the vehicle controlled by the sliding mode control. The vehicle controlled by the control allocation algorithm still has good handling and stability when one or more actuators are saturated or in a failure situation.

Fuzzy iterative learning control of electro-hydraulic servo system for SRM direct-drive volume control hydraulic press

A new kind of volume control hydraulic press that combines the advantages of both hydraulic and SRM(switched reluctance motor) driving technology is developed.Considering that the serious dead zone and time-variant nonlinearity exist in the volume control electro-hydraulic servo system,the ILC(iterative learning control) method is applied to tracking the displacement curve of the hydraulic press slider.In order to improve the convergence speed and precision of ILC,a fuzzy ILC algorithm that utilizes the fuzzy strategy to adaptively adjust the iterative learning gains is put forward.The simulation and experimental researches are carried out to investigate the convergence speed and precision of the fuzzy ILC for hydraulic press slider position tracking.The results show that the fuzzy ILC can raise the iterative learning speed enormously,and realize the tracking control of slider displacement curve with rapid response speed and high control precision.In experiment,the maximum tracking error 0.02 V is achieved through 12 iterations only.

Control of Multiple PWM Servos by a Single Programmable Timer

An algorithm for control of several servo motors by a mi- crocontroller is presented. The limited ntanber of progranunable timers on the majority of micnocntrollers presents a problem for multiple generation of timing pulses. Two software approaches are discussed in the paper and experimental results given for operation of a set of small servos using a single timer.

Modelling and Predictive Control of a Buck-Boost DC-DC Converter

A predictive current control algorithm for the Buck-Boost DC-DC converter is presented in this paper. The continuous time model of the system is properly introduced, then, by imposing a proper PWM modulation pattern, its discrete time model is achieved. This last one is successfully employed in determining the steady state locus of the Buck-Boost converter, both in CCM （continuous conduction mode） and DCM （discontinuous conduction mode）. A novel continuous time equivalent circuit of the converter is introduced too, with the aim of determining a ripple free representation of the state variables of the system, over both transient and steady state operation. Then, a predictive current control algorithm, suitable in both CCM and DCM, is developed and properly checked by means of computer simulations. The corresponding results have highlighted the effectiveness of the proposed modelling and of the predictive control algorithm, both in CCM and DCM.

Power Quality Improvement Using Grid Side Converter of Wind Energy Conversion System

This paper presents the control ofa WECS （wind energy conversion system）, equipped with a DFIG （doubly fed induction generator）, for maximum power generation and power quality improvement simultaneously. The proposed control algorithm is applied to a DFIG whose stator is directly connected to the grid and the rotor is connected to the grid through a back-to-back AC-DC-AC PWM （pulse width modulation） converter. The RSC （rotor side converter） is controlled in such a way to extract a maximum power, for a wide range of wind speed. The GSC （grid side converter） is controlled in order to filter harmonic currents of a nonlinear load coupled at the PCC （point of common coupling） and ensure smooth DC bus voltage. Simulation results show that the wind turbine can operate at its optimum energy for a wide range of wind speed and power quality improvement is achieved.

An uplink power control algorithm using traditional iterative model for cognitive radio networks

Based on the analysis of the feature of cognitive radio networks, a relevant interference model was built. Cognitive users should consider especially the problem of interference with licensed users and satisfy the signal-to-interference noise ratio （SINR） requirement at the same time. According to different power thresholds, an approach was given to solve the problem of coexistence between licensed user and cognitive user in cognitive system. Then, an uplink distributed power control algorithm based on traditional iterative model was proposed. Convergence analysis of the algorithm in case of feasible systems was provided. Simulations show that this method can provide substantial power savings as compared with the power balancing algorithm while reducing the achieved SINR only slightly, since 6% S1NR loss can bring 23% power gain. Through further simulations, it can be concluded that the proposed solution has better effect as the noise power or system load increases.

Research of the algorithm of the closed-loop control system to control the piezoelectric actuator

The piezoelectric actuator has been widely used in precision instruments and precision control. However, hysteresis, nonlinearity and creep exist in the actuator, which limit actuator applications and affect accuracy. This thesis introduces fuzzy control as the algorithm of a closed-loop control system to control the piezoelectric actuator. Fuzzy control can make this closed-looped system not only have high linearity, repeatability, accuracy and few overshoot, but isalso easily used.

A novel current vector decomposition controller design for six-phase permanent magnet synchronous motor

The vector control algorithm based on vector space decomposition （VSD） transformation method has a more flexible control freedom, which can control the fundamental and harmonic subspace separately. To this end, a current vector decoupling control algorithm for six-phase permanent magnet synchronous motor （PMSM） is designed. Using the proposed synchronous rotating coordinate transformation matrix, the fundamental and harmonic components in d-q subspace are changed into direct current （DC） component, only using the traditional proportional integral （PI） controller can meet the non-static difference adjustment, and the controller parameter design method is given by employing intemal model principle. In addition, in order to remove the 5th and 7th harmonic components of stator current, the current PI controller parallel with resonant controller is employed in x-y subspace to realize the specific harmonic component compensation. Simulation results verify the effectiveness of current decoupling vector controller.

Investigation of Shunt Active Power Filters in Railway Systems, Substation Installation

This paper investigates the performance of SAPFs （shunt active power filters） which are introduced in order to address the quality issues in electrified railway supply systems. These filters can be installed at either the S/S （substation） end or at the SP （sectioning post） of the railway feeding power system. In this investigation novel control algorithms, based on the synchronously rotating frame of reference, are proposed for the case when the SAPF is installed at the substation end and its performance is assessed. The effectiveness of the proposed control algorithms are illustrated via Matlab/SimPower computer simulations and validated via comparisons with other publications. This investigation demonstrated that when the SAPF is installed at the substation side, it can effectively compensate for the higher harmonic supply current. In addition, the reactive power demand is fully compensated for, leading to close to unity power factor. However, the voltage drop/sag at the locomotive power supply feed point is only partially compensated for.