Engineering Capabilities

Introduction

The overview from Open-house should go here.

Core Competencies

Control System Development Techniques

In the field of Mobile Hydraulics, we often solve problems that other approaches are not equipped to solve. Distributed, complex, and safe control systems are often only possible with model-based design. A controls primer is used to help explain key items to our controls offering. We are contrasting New Eagle's Model-Based Design approach against class Electro-Hydraulics controls development.

Control Systems Primer

Control engineering or control systems engineering is the engineering discipline that applies control theory to design systems with desired behaviors. The practice uses sensors to measure the output performance of the device being controlled (often a vehicle and sometimes called the “Plant”) and those measurements can be used to give feedback to the input actuators that can make corrections toward desired performance. When a device is designed to perform without the need of human inputs for correction it is called automatic control (such as cruise control for regulating a car's speed). Multi-disciplinary in nature, control systems engineering activities focus on implementation of control systems mainly derived by mathematical modeling of systems of a diverse range.

Open-Loop versus Closed-Loop Control

In most of the cases, control engineers utilize feedback when designing control systems. This is often accomplished using a PID controller system and called Closed-Loop. For example, in an automobile with cruise control the vehicle's speed is continuously monitored and fed back to the system, which adjusts the motor's torque accordingly. Where there is regular feedback, control theory can be used to determine how the system responds to such feedback. In practically all such systems stability is important and control theory can help ensure stability is achieved.

Although feedback is an important aspect of control engineering, control engineers may also work on the control of systems without feedback. This is known as open-loop control. A classic example of open loop control is a washing machine that runs through a pre-determined cycle without the use of sensors.

State Observer

In control theory, a state observer is a system that models a real system in order to provide an estimate of its internal state, given measurements of the input and output of the real system. It is typically a computer-implemented mathematical model. Knowing the system state is necessary to solve many control theory problems; for example, stabilizing a system using state feedback. In most practical cases, the physical state of the system cannot be determined by direct observation. Instead, indirect effects of the internal state are observed by way of the system outputs. A common example is vehicle speed sensing. A vehicle cannot measure its own speed but it can measure effects of the speed such as rotational wheel speed, and other states such as steering wheel angle. Based on these output measurements and the model of the vehicle, the vehicle speed can be continuously estimated. If a system is observable, it is possible to fully reconstruct the system state from its output measurements using the state observer.

A Primer Only

This section is intended to be a primer only, and does not include many of the additional concepts and approaches of New Eagle including Distributed systems, Adaptive Control, Gain Scheduling, Non-linear, and other topics.

New Eagle’s Electro-Hydraulics controls applications usually require a mix of open and closed-loop systems and observers. The complexity of each application usually requires custom software and approaches that are maintain efficient, fast, and cost effective solutions.

Model-Based Design and MotoHawk

New Eagle is an adherent of model-based design using Mathworks and the MotoHawk embedded system. In Electro-Hydraulics, our competition uses what we classify as Electro-Hydraulics programming techniques, which typically come from the former ladder logic world. There is a large class of problems to solve using these tools. However, we solve complex control problems that optimize the system using Model-based design techniques.

Some examples of E-H control using MotoHawk are found below.