Application Of Intelligent Control Techniques Research Articles

Improving primary frequency response in photovoltaic systems using hybrid inertia and intelligent control techniques

Abstract Low inertia poses a significant challenge to the widespread integration of photovoltaic (PV) systems into the grid, particularly affecting frequency stability. This paper addresses this challenge by proposing an advanced hybrid inertia (AHI) approach, characterized by the integration of real and virtual inertia, combined with the application of intelligent control techniques, to enhance the primary frequency response of a PV system. Internal inertia is provided by a synchronous generator (SG) acting as a compensator, while virtual inertia is generated through a real-time deloading strategy in the PV plant. The AHI is implemented on an isolated grid, utilizing various intelligent control techniques to improve frequency stability. The intelligent techniques employed include genetic algorithms (GA) and fuzzy logic controllers (FLC), which do not require mathematical modeling. This allows them to overcome the nonlinear dynamics of the PV plant and the uncertainties associated with climatic changes. These techniques are applied to the nonlinear components on the generator side, including the governor loop, DC-DC converter loop, and power reserve injection management loop. A frequency fluctuation scenario, induced by generating power perturbations in the proposed system, demonstrates and validates the improvement in frequency stability achieved by the HI and intelligent techniques. All tests are conducted using MATLAB Simulink. Various simulation results show a significant improvement in frequency stability through the incorporation of HI and intelligent control techniques.

Design and experiment of bionic stubble breaking-deep loosening combined tillage machine

Under the conditions of straw returning operation, there are three major technical bottlenecks in the Phaeozem region of northeast China, namely low stubble breaking rate, poor tillage depth consistency and high fuel consumption. In this research, a bionic stubble-deep loosening combined tillage machine (BSD) was designed through bionic prototype analysis, coupled bionic analysis, coupled bionic design, theoretical analysis and application of intelligent control techniques. It consists of a bionic stubble breaking device and a bionic self-excited vibratory deep loosening device. Based on the unique biting pattern of locust mouthparts on maize rootstocks, the bionic stubble breaking device adopted a new multi-segment serrated bionic structure and a symmetrical rotational motion, which could significantly increase the stubble breaking rate (p<0.05) and reduce the resistance to stubble breaking operations (p<0.05). Based on the unique biology of the hare's paws, toes and nails, the bionic self-excited vibration deep loosening device adopted a new series-parallel composite bionic elastic system and an intelligent tilling depth control system with a fuzzy algorithm, which significantly improved the tilling depth consistency (p<0.05). The operational performance of the BSD was verified at different operating speeds through comparative experiments and reveals the mechanism of its excellent performance through theoretical analysis. The final experiment results showed that, at the same operating speed, the BSD improved the stubble breaking rate by 9.62% and 10.67%, reduced the stubble breaking torque by 28 N·m and 33 N·m, reduced the tillage depth coefficient of variation by 12.73% and 13.48%, and reduced the specific fuel consumption by 36 g/km·h and 40 g/km·h compared to the two most common models. The operating performance of the three kinds of machines will decrease with the increase of operating speed, and the BSD has the least decrease. Keywords: bionics, stubble breaking, deep loosening, combined tillage machine DOI: 10.25165/j.ijabe.20211404.6473 Citation: Zhao J L, Lu Y, Guo M Z, Fu J, Wang Y J. Design and experiment of bionic stubble breaking-deep loosening combined tillage machine. Int J Agric & Biol Eng, 2021; 14(4): 123–134.

Design and experiment of bionic stubble breaking-deep loosening combined tillage machine

Under the conditions of straw returning operation, there are three major technical bottlenecks in the Phaeozem region of northeast China, namely low stubble breaking rate, poor tillage depth consistency and high fuel consumption. In this research, a bionic stubble-deep loosening combined tillage machine (BSD) was designed through bionic prototype analysis, coupled bionic analysis, coupled bionic design, theoretical analysis and application of intelligent control techniques. It consists of a bionic stubble breaking device and a bionic self-excited vibratory deep loosening device. Based on the unique biting pattern of locust mouthparts on maize rootstocks, the bionic stubble breaking device adopted a new multi-segment serrated bionic structure and a symmetrical rotational motion, which could significantly increase the stubble breaking rate (p<0.05) and reduce the resistance to stubble breaking operations (p<0.05). Based on the unique biology of the hare's paws, toes and nails, the bionic self-excited vibration deep loosening device adopted a new series-parallel composite bionic elastic system and an intelligent tilling depth control system with a fuzzy algorithm, which significantly improved the tilling depth consistency (p<0.05). The operational performance of the BSD was verified at different operating speeds through comparative experiments and reveals the mechanism of its excellent performance through theoretical analysis. The final experiment results showed that, at the same operating speed, the BSD improved the stubble breaking rate by 9.62% and 10.67%, reduced the stubble breaking torque by 28 N·m and 33 N·m, reduced the tillage depth coefficient of variation by 12.73% and 13.48%, and reduced the specific fuel consumption by 36 g/km·h and 40 g/km·h compared to the two most common models. The operating performance of the three kinds of machines will decrease with the increase of operating speed, and the BSD has the least decrease. Keywords: bionics, stubble breaking, deep loosening, combined tillage machine DOI: 10.25165/j.ijabe.20211404.6473 Citation: Zhao J L, Lu Y, Guo M Z, Fu J, Wang Y J. Design and experiment of bionic stubble breaking-deep loosening combined tillage machine. Int J Agric & Biol Eng, 2021; 14(4): 123–134.

Voltage Control in Active Distribution Networks Under Uncertainty in the System Model: A Robust Optimization Approach

Within the context of ancillary services for active distribution networks (ADNs), application of intelligent control techniques is required in order to achieve specific operation objectives. Despite their differences, most control mechanisms proposed in the literature rely on the assumption that the distribution network operator has an accurate and up-to-date model of the network topology and a complete knowledge of the line parameters, i.e., a correct network admittance matrix Y. However, this assumption does not always hold in reality due to both an incomplete knowledge of the grid asset and/or a physical change of the line parameters. In this paper, we consider the problem of optimal voltage control in ADNs under uncertain, but bounded, line parameters with no assumptions on the parameters’ uncertainty distribution. In particular, availability of a monitoring infrastructure is assumed and the goal is to control the active and reactive power injections of a number of distributed generators connected to the network buses in coordination with the transformers on-load tap changers. The optimal control problem is formulated as a mixed-integer linear problem by means of sensitivity coefficients and a robust optimization framework is used in order to account for the uncertainties in the network admittance matrix. In order to estimate the benefits of the proposed method, the evaluation of the algorithm is carried out by using both the IEEE 13- and the IEEE 34-nodes test feeder.

Development of an autonomous in‐pipe robot for offshore pipeline maintenance

PurposeThe purpose of this paper is to develop a novel autonomous in‐pipe robot to perform the preventive point reparation for long‐distance offshore oil pipelines.Design/methodology/approachThe autonomous in‐pipe robot performs online ultrasonic inspection for pipe wall thickness, and the original inspection data are stored in large capacity hard disk. Through the offline data analysis by the data analysts and the software tool, the pipeline health status is known. If server defects lie there, the in‐pipe robot is introduced into the pipeline once more to indicate the defect's location to the maintenance ship.FindingsThe laboratory tests and the field tests prove the feasibility and validity of the developed autonomous in‐pipe robot. Furthermore, the application of intelligent control techniques ensures the mission completion by the autonomous in‐pipe robot, which worked in the awful pipeline environment.Practical implicationsThe developed autonomous in‐pipe robot helps eliminate lost production costs and pipeline downtime caused by leakages and guarantees the safe run of offshore oil pipelines.Originality/valueFor the application of the autonomous in‐pipe robot, there are no special requirements for maintained pipelines themselves, so it is applicable to the point reparation for most long‐distance welded offshore pipelines.

SURVEY OF INTELLIGENT CONTROL ALGORITHMS FOR HUMANOID ROBOTS

This paper focusses on the application of intelligent control techniques (neural networks, fuzzy logic and genetic algorithms) and their hybrid forms (neuro-fuzzy networks, neuro-genetic and fuzzy-genetic algorithms) in the area of humanoid robotic systems. Overall, this survey covers a broad selection of examples that will serve to demonstrate the advantages and disadvantages of the application of intelligent control techniques.

Survey of Intelligent Control Techniques for Humanoid Robots

This paper focusses on the application of intelligent control techniques (neural networks, fuzzy logic and genetic algorithms) and their hybrid forms (neuro-fuzzy networks, neuro-genetic and fuzzy-genetic algorithms) in the area of humanoid robotic systems. It represents an attempt to cover the basic principles and concepts of intelligent control in humanoid robotics, with an outline of a number of recent algorithms used in advanced control of humanoid robots. Overall, this survey covers a broad selection of examples that will serve to demonstrate the advantages and disadvantages of the application of intelligent control techniques.

Intelligent robotic control

A theoretical approach is developed to deal with man-machine interactive systems requiring advanced decision making in unpredictable environments. The hierarchical method consists of a three-layer control of increasing intelligence and decreasing precision. The lowest level consists of several controllers designed for effective control with existing hardware using an approximation theory of optimal control. The next level is that of a coordinator which utilizes new computer architectures to effectively control the overall hardware system. The highest level is the organizer which supervises the performance of the overall system. Both highest levels are computer implemented and the research involved is in developing the appropriate architecture and software to accommodate others. The lowest level, aimed for end-point control tasks, is dominated by typical hardware control methods. The coexistence of the two approaches makes the method novel. Application of intelligent control techniques to robotics and manipulative systems is considered.