Autonomous Load Profile Recognition in Industrial DC-Link Using an Audio Search Algorithm

Industrial manufacturing plants, including machine tools, robots, and elevators, perform dynamic acceleration and braking processes. Recuperative braking results in an increased voltage in the machines' direct current (DC) links. In the case of a diode rectifier, a braking resistor turns the surplus of energy into lost heat. In contrast, active rectifiers can feed the braking energy back to the AC grid, though they are more expensive than diode rectifiers. DC link-coupled energy storage systems are one possible solution to downsize the supply infrastructure by peak shaving and to harvest braking energy. However, their control heavily depends on the applied load profiles that are not known in advance. Especially for retrofitted energy storage systems without connection to the machine control unit, load profile recognition imposes a major challenge. A self-tuning framework represents a suitable solution by covering system identification, proof of stability, control design, load profile recognition, and forecasting at the same time. This paper introduces autonomous load profile recognition in industrial DC links using an audio search algorithm. The method generates fingerprints for each measured load profile and saves them in a database. The control of the energy storage system then has to be adapted within a critical time range according to the identified load profile and constraints given by the energy storage system. Three different load profiles in four case studies validate the methodology

Design, Control, and Optimization of Robots with Advanced Energy Regenerative Drive Systems

We investigate the control and optimization of robots with ultracapacitor based regenerative drive systems. A subset of the robot joints are conventional, in the sense that external power is used for actuation. Other joints are energetically self-contained passive systems that use ultracapacitors for energy storage. An electrical interconnection known as the star configuration is considered for the regenerative drives that allows for direct electric energy redistribution among joints, and enables higher energy utilization efficiencies. A semi-active virtual control strategy is used to achieve control objectives. We find closed-form expressions for the optimal robot and actuator parameters (link lengths, gear ratios, etc.) that maximize energy regeneration between any two times, given motion trajectories. In addition, we solve several trajectory optimization problems for maximizing energy regeneration that admit closed-form solutions, given system parameters. Optimal solutions are shown to be global and unique. In addition, closed-form expressions are provided for the maximum attainable energy. This theoretical maximum places limits on the amount of energy that can be recovered. Numerical examples are provided in each case to demonstrate the results. For problems that don\u27t admit analytical solutions, we formulate the general nonlinear optimal control problem, and solve it numerically, based on the direct collocation method. The optimization problem, its numerical solution and an experimental evaluation are demonstrated using a PUMA manipulator with custom regenerative drives. Power flows, stored regenerative energy and efficiency are evaluated. Experimental results show that when following optimal trajectories, a reduction of about 10-22% in energy consumption can be achieved. Furthermore, we present the design, control, and experimental evaluation of an energy regenerative powered transfemoral prosthesis. Our prosthesis prototype is comprised of a passive ankle, and an active regenerative knee joint. A novel varying impedance control approach controls the prosthesis in both the stance and swing phase of the gait cycle, while explicitly considering energy regeneration. Experimental evaluation is done with an amputee test subject walking at different speeds on a treadmill. The results validate the effectiveness of the control method. In addition, net energy regeneration is achieved while walking with near-natural gait across all speeds