Integrated Channel-Aware Scheduling and Packet-Based Predictive Control for Wireless Cloud Control Systems

2020 ◽  
pp. 1-15
Author(s):  
Pengfei Li ◽  
Yun-Bo Zhao ◽  
Yu Kang
Keyword(s):  
Control Systems ◽  
Predictive Control ◽  
Wireless Cloud ◽  
Channel Aware Scheduling

Predictive, Deadbeat, and Combined Controls

2018 ◽  
Author(s):  
Sadegh Vaez-Zadeh
Keyword(s):  
Control Systems ◽  
Predictive Control ◽  
Direct Torque Control ◽  
Fast Response ◽  
Torque Control ◽  
Control Methods ◽  
Electric Motors ◽  
Operating Cycle ◽  
Combined Control ◽  
The One

In this chapter, three control methods recently developed for or applied to electric motors in general and to permanent magnet synchronous (PMS) motors, in particular, are presented. The methods include model predictive control (MPC), deadbeat control (DBC), and combined vector and direct torque control (CC). The fundamental principles of the methods are explained, the machine models appropriate to the methods are derived, and the control systems are explained. The PMS motor performances under the control systems are also investigated. It is elaborated that MPC is capable of controlling the motor under an optimal performance according to a defined objective function. DBC, on the other hand, provides a very fast response in a single operating cycle. Finally, combined control produces motor dynamics faster than one under VC, with a smoother performance than the one under DTC.

Direct Longitudinal Force Feedback for High-Performance Vehicle Dynamics Control Systems

2021 ◽  
Author(s):  
Giorgio Riva ◽  
Luca Mozzarelli ◽  
Matteo Corno ◽  
Simone Formentin ◽  
Sergio M. Savaresi
Keyword(s):  
Model Predictive Control ◽  
Control Systems ◽  
Predictive Control ◽  
Vehicle Dynamics ◽  
High Performance ◽  
Force Feedback ◽  
Longitudinal Force ◽  
Spiral Path ◽  
Comparable Performance ◽  
Vehicle Dynamics Control

Abstract State of the art vehicle dynamics control systems do not exploit tire road forces information, even though the vehicle behaviour is ultimately determined by the tire road interaction. Recent technological improvements allow to accurately measure and estimate these variables, making it possible to introduce such knowledge inside a control system. In this paper, a vehicle dynamics control architecture based on a direct longitudinal tire force feedback is proposed. The scheme is made by a nested architecture composed by an outer Model Predictive Control algorithm, written in spatial coordinates, and an inner longitudinal force feedback controller. The latter is composed by four classical Proportional-Integral controllers in anti-windup configuration, endowed with a suitably designed gain switching logic to cope with possible unfeasible references provided by the outer loop, avoiding instability. The proposed scheme is tested in simulation in a challenging scenario where the tracking of a spiral path on a slippery surface and the timing performance are handled simultaneously by the controller. The performance is compared with that of an inner slip-based controller, sharing the same outer Model Predictive Control loop. The results show comparable performance in presence of unfeasible force references, while higher robustness is achieved with respect to friction curve uncertainties.

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