Wireless control system simulation and network adaptive control

Abstract

With the arrival of the wireless automation standards WirelessHART and ISA100.11a, the use of wireless technology in the automation industry is emerging today. The main benefits of using wireless devices range from no cable and lower installation costs to more flexible positioning. When using next generation agile wireless communication methods in control applications, the unreliability of the wireless network becomes an issue, due to the real-time requirements of control. The research has previously focused on either control design and stability for wired control, or network protocols for wireless sensor networks. A marginal part of the research has studied wireless control. This thesis takes a practical approach to the field of wireless control design. A simulation system called PiccSIM is developed, where the communication and control can be co-simulated and studied. There already exists some simulation tools, such as TrueTime, but none of them delivers as flexible and versatile capabilities as PiccSIM for simulation of specific protocols and algorithms. PiccSIM is not only a simulation system: it consists of a tool-chain for network and control design, and further implementation for real wireless nodes. A variety of wireless control scenarios are simulated and studied. The effects of the network on the control performance are studied both theoretically and through simulations to gain an insight into the communication and control interaction. Typical control design approaches in the literature are of optimal control-type, with guaranteed stability given certain network induced delay and packet losses. The control design has been complicated and resulted in complex controllers. This thesis concentrates on PID-type controllers, because of their simplicity and wide use in industry. To accommodate PID controllers to control over unreliable wireless networks, several adaptive schemes, which adapt to the network quality of service, are developed. This results in flexible, self-tuning control that can cope with non-deterministic and time-varying wireless networks. The proposed adaptive control algorithms are tested and verified in simulations using PiccSIM.