On the gain scheduling for networked PI controller over IP network

The potential use of networks for real-time high-performance control and automation is enormous and appealing. Replacing a widely used proportional-integral (PI) controller by a new networked controller for networked control capability can be costly and time-consuming. This paper proposes a methodology based on gain scheduling with respect to real-time IP traffic conditions to enhance the existing PI controller so it can be used over IP networks with a general network protocol like Ethernet. This paper first describes the gain scheduling approach based on constant network delays using a rational function approach. The formulation is extended to random IP network round-trip time (RTT) delays by using the generalized exponential distribution model. Simulation results show that the PI controller with gain scheduling provides significantly better networked control system performance.     

Neural-network-based motor rolling bearing fault diagnosis

Motor systems are very important in modern society. They convert almost 60% of the electricity produced in the US into other forms of energy to provide power to other equipment. In the performance of all motor systems, bearings play an important role. Many problems arising in motor operations are linked to bearing faults. In many cases, the accuracy of the instruments and devices used to monitor and control the motor system is highly dependent on the dynamic performance of the motor bearings. Thus, fault diagnosis of a motor system is inseparably related to the diagnosis of the bearing assembly. In this paper, bearing vibration frequency features are discussed for motor bearing fault diagnosis. This paper then presents an approach for motor rolling bearing fault diagnosis using neural networks and time/frequency-domain bearing vibration analysis. Vibration simulation is used to assist in the design of various motor rolling bearing fault diagnosis strategies. Both simulation and real-world testing results obtained indicate that neural networks can be effective agents in the diagnosis of various motor bearing faults through the measurement and interpretation of motor bearing vibration signatures     

Gain adaptation of networked DC motor controllers based on QoS variations

Connecting a complex control system with various sensors, actuators, and controllers as a networked control system by a shared data network can effectively reduce complicated wiring connections. This system is also easy to install and maintain. The trend is to use networked control systems for time-sensitive applications, such as remote DC motor actuation control. The performance of a networked control system can be improved if the network can guarantee quality-of-service (QoS). Due to time-varying network traffic demands and disturbances, QoS requirements provided by a network may change. In this case, a network has to reallocate its resources and may not be able to provide QoS requirements to a networked control application as needed. Therefore, the application may have to gracefully degrade its performance and perform the task as best as possible with the provided network QoS. This paper proposes a novel approach for networked DC motor control systems using controller gain adaptation to compensate for the changes in QoS requirements. Numerical and experimental simulations, and prototyping, are presented to demonstrate the feasibility of the proposed adaptation scheme to handle network QoS variation in a control loop. The effective results show the promising future of the use of gain adaptation in networked control applications.     

Gain scheduler middleware: a methodology to enable existing controllers for networked control and teleoperation - part I: networked control

Conventionally, in order to control an application over a data network, a specific networked control or teleoperation algorithm to compensate network delay effects is usually required for controller design. Therefore, an existing controller has to be redesigned or replaced by a new controller system. This replacement process is usually costly, inconvenient, and time consuming. In this paper, a novel methodology to enable existing controllers for networked control and teleoperation by middleware is introduced. The proposed methodology uses middleware to modify the output of an existing controller based on a gain scheduling algorithm with respect to the current network traffic conditions. Since the existing controller can still be utilized, this approach could save much time and investment cost. Two examples of the middleware applied for networked control and teleoperation with IP network delays are given in these two companion papers. Part I of these two companion papers introduces the concept of the proposed middleware approach. Formulation, delay modeling, and optimal gain finding based on a cost function for a case study on DC motor speed control with a proportional-integral (PI) controller are also described. Simulation results of the PI controller shows that, with the existence of IP network delays, the middleware can effectively maintain the networked control system performance and stabilize the system. Part II of this paper will cover the use of the proposed middleware concept for a mobile robot teleoperation.     

Gain scheduler middleware: a methodology to enable existing controllers for networked control and teleoperation-part II: teleoperation

This paper is the second of two companion papers. The foundation for the external gain scheduling approach to enable an existing controller via middleware for networked control with a case study on a proportional-integral (PI) controller for dc motor speed control over IP networks was given in Part I. Part II extends the concepts and methods of the middleware called gain scheduler middleware (GSM) in Part I to enable an existing controller for mobile robot path-tracking teleoperation. By identifying network traffic conditions in real-time, the GSM will predict the future tracking performance. If the predicted tracking performance tends to be degraded over a certain tolerance due to network delays, the GSM will modify the path-tracking controller output with respect to the current traffic conditions. The path-tracking controller output is modified so that the robot will move with the fastest possible speed, while the tracking performance is maintained in a certain tolerance. Simulation and experimental results on a mobile robot path-tracking platform show that the GSM approach can significantly maintain the robot path-tracking performance with the existence of IP network delays.