Multivariable Control of an Earthmoving Vehicle Powertrain Experimentally Validated in an Emulated Working Cycle

Author(s):  
Rong Zhang ◽  
Don E. Carter ◽  
Andrew G. Alleyne

The operation of an earthmoving vehicle involves the coordination of a multivariable powertrain and the execution of specific tasks in a repetitive fashion. The performance and efficiency depend heavily on human expertise. The purpose of this research is to automate the coordination of a multi-input multi-output (MIMO) nonlinear electro-hydraulic powertrain and to validate the performance and efficiency improvements in a human-machine interaction. Firstly, a robust gain scheduling method is developed to design a powertrain controller and to analyze its robust stability and robust performance. The gain scheduling is based on a Local Controller Network strategy and its satisfactory properties are analytically confirmed using robust control theories. Secondly, the improvement of performance and efficiency are validated through two experiments performed on an Earthmoving Vehicle Powertrain Simulator (EVPS). This testbed is a Hardware-In-the-Loop HIL environment representative of a class of electro-hydraulic systems with multiple loads. The two human-operated experiments include a reference tracking test and a working cycle test. In the second test, three types of loads are modeled for a typical wheel loader and emulated on EVPS for a 180-degree loading cycle. These models include the steering, the drive, and the implement. The load emulation technique ensures that the HIL working cycles are representative of real life cycles. The reference tracking and loading cycle results show the significant improvement in productivity in terms of performance, efficiency, and ease of operation.

Object detection (OD) within a video is one of the relevant and critical research areas in the computer vision field. Due to the widespread of Artificial Intelligence, the basic principle in real life nowadays and its exponential growth predicted in the epochs to come, it will transmute the public. Object Detection has been extensively implemented in several areas, including human-machine Interaction, autonomous vehicles, security with video surveillance, and various fields that will be mentioned further. However, this augmentation of OD tackles different challenges such as occlusion, illumination variation, object motion, without ignoring the real-time aspect that can be quite problematic. This paper also includes some methods of application to take into account these issues. These techniques are divided into five subcategories: Point Detection, segmentation, supervised classifier, optical flow, a background modeling. This survey decorticates various methods and techniques used in object detection, as well as application domains and the problems faced. Our study discusses the cruciality of deep learning algorithms and their efficiency on future improvement in object detection topics within video sequences.


Models are expected to present near real life situations and possible effects on the deliverables based on given input environment. However, models do not necessarily indicate the true solutions and provide scope to work on them incrementally. As discussed earlier, organizations may not follow similar paths to acquire IT and may not even derive desired results despite adopting one. This chapter considers it important to include IS as critical input to managing IT acquisition life cycles and delves further into the IT life cycle management principles to conceptualize a model to specific contributions to assess organizational preparedness for IT acquisitions. This model largely includes discussions on IS centric models and argues in favour of assessing the preparedness across three phases, pre-acquisition, acquisition, and post-acquisition. Each phase considers specific inputs with expected deliverables for successful assessment of the preparedness of the organization in that phase.


Author(s):  
E Prempain ◽  
I Postlethwaite

This paper considers the design of two-degree-of-freedom gain-scheduled controllers for a helicopter system in a new fashion. By taking advantage of a two-degree-of-freedom decoupling scheme, it is possible to generically split the controller synthesis into two parts. One part is concerned with the synthesis of a regulator and the other aims to achieve the tracking requirements. An important feature of the method is that the feedforward filter can be designed by solving a particular full information problem. A robust linear time-invariant (LTI) regulator will be designed and two methods used to synthesize a gain-scheduled feedforward tracking controller will be investigated. The first method is based on a quadratic gain scheduling technique which makes use of a polytopic description of the plant. The second is simpler and uses the concept of linear interpolation of LTI controllers. Both methods are tested on a Lynx MK7 helicopter in simulation. For this application, the benefits and the shortcomings of the respective methods are discussed. Non-linear simulation results show that the gain-scheduled interpolated controller performs remarkably well over the flight envelope.


2009 ◽  
Vol 8 (1) ◽  
pp. 62-71 ◽  
Author(s):  
Nancy Dumais ◽  
Abdelkrim Hasni

Understanding real-life issues such as influenza epidemiology may be of particular interest to the development of scientific knowledge and initiation of conceptual changes about viruses and their life cycles for high school students. The goal of this research project was to foster the development of adolescents' conceptual understanding of viruses and influenza biology. Thus, the project included two components: 1) pre- and posttests to determine students' conceptions about influenza biology, epidemics/pandemics, and vaccination; and 2) design an intervention that supports conceptual change to promote improvements in influenza knowledge based on these primary conceptions. Thirty-five female students from a high school biology class participated in a series of instructional activities and pre- and posttest assessments. Results from the pretest indicated that high school students exhibit a limited understanding of concepts related to viruses. Six weeks after an intervention that promoted active learning, results from a posttest showed that conceptions about influenza are more accurately related to the provided scientific knowledge. Although adolescents have nonscientific models to explain influenza biology, we showed that a carefully designed intervention can affect students' knowledge as well as influence the implementation of health education programs in secondary schools.


Author(s):  
Cem Onat ◽  
Mahmut Daskin ◽  
Abdullah Turan

In different industrial processes in which position and force control are desired, electro-hydraulic systems have a widespread area of utilization. Models of electro-hydraulic systems include high order nonlinearity. In this study, a gain scheduling linear model corresponded with nonlinear model of a hydraulic force actuator system is developed. The proposed model is constituted in two distinct and consecutive stages. In the first step, nonlinear terms caused to nonlinearity are described by the means of measurable or observable system parameters and embedded in a nonlinear scheduling parameter. Thus, the scheduling parameter is continuously extracted from main system. In the second step, the nonlinear system equation is rearranged by the scheduling parameter and by this way parameter varying linear model is obtained. The simulations which are performed by use of Matlab-Simulink computer program show that the proposed model rightly fits to the nonlinear system model.


Author(s):  
Ayesha Maroof ◽  
Adnan Tariq ◽  
Sahar Noor

Shorter product life cycles, unpredictable demand patterns and the ever-shrinking time to market, have been constantly keeping the manufacturing firms under a lot of pressure. To face these challenges the manufacturing organizations have been shifting to Cellular Manufacturing (CM) due to its benefits of reducing manufacturing costs, increasing flexibility and delivering orders on time. Despite having several benefits, designing a Cellular Manufacturing System (CMS) for a real-life application is a tough ask. The main challenge is the part-machine grouping in cells. It becomes even more challenging when the group scheduling (GS) problem is handled alongside the part-machine clustering. To take up this challenge, an integrated model is developed during this research which handles the machine-part grouping and the GS problems, simultaneously. To optimize the multiple objectives of maximizing Grouping Efficacy (GE) and minimizing Makespan (Cmax), concurrently, a Hybrid Genetic Algorithm (HGA) based approach is developed. The proposed technique is validated through the famous benchmark problems, unlike the several approaches already available in literature. The computational results have shown that the integrated approach, presented in this paper, is more effective as compared to a sequential technique. Also, its accuracy remains intact even if it is applied to large sized problems.


Author(s):  
Валентин Сидоренко ◽  
Valentin Sidorenko ◽  
Максим Полешкин ◽  
Maksim Poleshkin ◽  
Владимир Антоненко ◽  
...  

The tutorial discusses the basics of building hydro-mechanical systems, the composition of their components, the functional description, the element base, the methods for calculating the basic parameters and the determination of the characteristics of the elements of hydraulic systems. The study of circuit solutions of process equipment requires knowledge of the principles of operation of individual elements of the hydraulic drive: power sources, hydraulic motors, control, guide and control equipment, auxiliary devices. Presented hydroficated mobile and stationary technological equipment, allows for the example of real-life facilities to consolidate knowledge of the synthesis and analysis of hydro-mechanical systems.


Author(s):  
Shuzhong Zhang ◽  
Tatiana Minav ◽  
Matti Pietola

Government regulations incentivize investigation of the potential for hybridization of non-road mobile machinery (NRMM). Many approaches to energy saving in hydraulic systems have been established. One of the methods first introduced in the aerospace industry is “decentralized” or “zonal” hydraulics. The decentralized system is realized with pump-controlled actuators, which are distributed throughout the system. In this research, decentralized hydraulics are realized with a direct-driven hydraulics (DDH) drive and implemented on a 1-ton class JCB micro excavator. The original valve-controlled system for boom, stick, and bucket is replaced with three DDH units. In a DDH unit, a double fixed displacement pump/motors with a speed-controlled electric servomotor directly controls the amount of hydraulic oil pumped into and out of the system. The hydraulic pump/motors create flows dependant on the rotating speed of the servomotor. A hydraulic accumulator is used as a conventional tank replacement. The aim of this paper is to investigate the efficiency improvement of the excavator with decentralized hydraulics compared to an electrified conventional load sensing system, from an energy consumption point of view under a typical digging cycle. In order to acquire the energy consumption distributions of the DDH and load sensing (LS) system, a model of the micro excavator which comprises mechanics, hydraulics, electronics, and control systems is developed in Matlab/Simulink. Simulation results demonstrate that the total efficiency of the excavator with LS control is 18.3%, and with DDH (decentralized hydraulics) is 71.3 % for a selected typical working cycle.


Vehicles ◽  
2020 ◽  
Vol 2 (4) ◽  
pp. 625-647
Author(s):  
Yash Raj Khusro ◽  
Yanggu Zheng ◽  
Marco Grottoli ◽  
Barys Shyrokau

Driving simulators are widely used for understanding human–machine interaction, driver behavior and in driver training. The effectiveness of simulators in this process depends largely on their ability to generate realistic motion cues. Though the conventional filter-based motion-cueing strategies have provided reasonable results, these methods suffer from poor workspace management. To address this issue, linear MPC-based strategies have been applied in the past. However, since the kinematics of the motion platform itself is nonlinear and the required motion varies with the driving conditions, this approach tends to produce sub-optimal results. This paper presents a nonlinear MPC-based algorithm which incorporates the nonlinear kinematics of the Stewart platform within the MPC algorithm in order to increase the cueing fidelity and use maximum workspace. Furthermore, adaptive weights-based tuning is used to smooth the movement of the platform towards its physical limits. Full-track simulations were carried out and performance indicators were defined to objectively compare the response of the proposed algorithm with classical washout filter and linear MPC-based algorithms. The results indicate a better reference tracking with lower root mean square error and higher shape correlation for the proposed algorithm. Lastly, the effect of the adaptive weights-based tuning was also observed in the form of smoother actuator movements and better workspace use.


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