Variable speed refrigeration systems have the potential for improved energy savings compared to conventional on-off systems. A single-input-single-output (SISO) control structure does not adequately regulate control parameters due to strong coupling inherent to the vapor compression cycle (VCC). With the use of an electronic expansion valve (EEV) a feedforward control configuration may be implemented to remove the effects of compressor speed changes on evaporator superheat, thus allowing better regulation during transients. Due to the nonlinearity of the VCC a scheduled feedforward compensator is proposed to effectively reject a compressor disturbance over the wide range of operating conditions typically experienced by variable speed systems. The proposed control structure allows superheat regulation at a low level without risking compressor damage, therefore helping maximize system efficiency. This paper presents experimental results obtained through load emulation. This is a novel approach which performs a task similar to the automotive dynamometer, where various size loads and environmental conditions may be placed on a VCC through an on-line experimental simulation.

The friction stir welding procedure to seal copper canisters requires variable power input throughout the 45 minute long weld cycle to keep the welding temperature within the process window. This is due to variable thermal boundary conditions throughout the weld cycle which, together with fast disturbances in the spindle torque, requires control of both the power input and the welding temperature to achieve a stable and robust process. By using a cascaded loop that determines the power input requirement, the regulator will not be dependent on repeatability in the necessary power input between weld cycles. As a result, a more accurate and reliable closed-loop control of the welding temperature is acquired.

Proportional-Integral-Derivative (PID) control has been most commonly used to operate mechanical systems. In PID control, however, there are limits to the accuracy of the resulting movement because of the influence of gravity, friction, and interaction of joints. We have proposed a digital acceleration control (DAC) that is robust over these modeling errors. One of the most practicable advantages of DAC is robustness against modeling errors. However, it does not always work effectively. If there are modeling errors in the inertia term of the model, the DAC controller cannot control a mechanical system properly. Generally an inertia term is easily modeled in advance, but it has a possibility to change. Therefore, we propose an online estimation method of an inertia term by using a system identification method. By using the proposed method, the robustness of DAC is considerably improved. This paper shows the simulation results of the proposed method using 2-link manipulator.

In human-machine cooperation, machines may assist operators in a variety of ways. This paper discusses the coordination of various assistances on cognitive basis through a PID-based control approach. Cognitive assistance can be viewed as a two-dimensional problem. The question of when to provide assistance can be viewed as a control problem, and the question of what assistance to provide can be viewed as an interface problem. This research proposes pairing cognitive engagement level and performance relevant situation criticality with a PID control approach to determine the appropriate moment to provide proper assistance. Based on the stage of human cognitive processing, the interfaces of cognitive assistance are grouped into three levels: soft aid, soft intervention, and hard intervention. This paper took driving assistance as an exemplary application to validate the approach of cognitive assistances coordination. In the experiment, an intelligent machine driver monitored drivers’ real-time performance by measuring the time headway to front obstacles and the lateral deviation to lane center. Simultaneously, it monitored drivers’ cognitive state by measuring the eye movement with an eye tracker. With five sessions of driving, coordinated cognitive assistance was compared with no aid, soft aid, soft intervention, and hard intervention, respectively. The experimental results confirmed that coordinated cognitive assistance is the most effective approach to assist both primary and secondary tasks. It also proves to be a more enjoyable and less obtrusive assistance system when compared to other individual types of assistance. In addition, coordinated cognitive assistance can be extended to other real-time control relevant tasks.

Cherrypickers are an important class of machines that can lift people to great heights. Understanding the dynamics and stability of these machines is crucial for efficient and safe operation. A dynamic model has been developed to capture the oscillatory dynamics of the machine as a function of the configuration and mass properties. Simulation studies reveal the complex dynamic behavior of the machine. In many cases, the oscillation of the endpoint bucket causes difficulties and dangers for the operators. An input-shaping controller has been added to the system to decrease the oscillatory dynamics. A portable cherrypicker is being developed for use in both education and research. The cherrypicker will be used as an experimental testbed in an advanced controls course at the Massachusetts Institute of Technology. The MIT students will use the machine to verify their theoretical models of the dynamic behavior, as well as evaluate control systems they develop to improve performance. Concurrently, students at the Georgia Institute of Technology will use the machine in teleoperation mode to conduct similar experiments. The MIT and Georgia Tech students will work together to conduct meaningful research on the cherrypicker testbed for their course projects. This paper describes the developments and results of the project to date.