A Fuzzy Control Load Balancing Method for Dual CAN Bus
This chapter presents a load balancing method for dual CAN bus to maximize the use of network bandwidth. The CAN (controller area network) is a serial communication protocol gaining widespread acceptance in automotive and automation industry. The network uses dual bus to improve network bandwidth and performance. The data traffic of CAN bus is degraded on high-load conditions. This chapter proposes a load balancing allocation algorithm using fuzzy control to obtain the maximum data traffic. The load balancing allocation algorithm introduced in the chapter is validated on a four-node dual CAN bus system. Each CAN node uses a LPC2119 ARM development board as hardware platform. The chip LPC2119 is based on the ARM7 CPU core with 2 CAN channels. Experiment results show that the fuzzy control is quite suitable for the load balancing control to improve the performance of dual CAN bus at high-load conditions.
KeywordsDual CAN bus Fuzzy control Load balancing
This study was funded by grants from Foxnum Technology Co., Ltd. (project no. 302205501), so that the study can be completed smoothly.
- 1.Gao X, Li L (2011) Analysis and research of real time ability of message transmission in CAN bus. In: International conference on control, automation and systems engineering (CASE), IEEE Press, New York, 2011, pp 1–3Google Scholar
- 2.Nolte T, Hansson H, Norstrom C (2003) Probabilistic worst-case response-time analysis for the controller area network. In: The 9th IEEE real-time and embedded technology and applications symposium, IEEE Press, New York, 2003, pp 200–207Google Scholar
- 3.Davis RI, Navet N (2012) Controller area network (CAN) schedulability analysis for messages with arbitrary deadlines in FIFO and work-conserving queues. In: 2012 9th IEEE international workshop on factory communication systems (WFCS), EEE Press, New York, 2012, pp 33–42Google Scholar
- 4.Jun Y, Kai X (2010) The application of fuzzy control in solar heat supply and storage system. In: 2010 international conference on computer, mechatronics, control and electronic engineering (CMCE), IEEE Press, New York, 2010, pp 179–182Google Scholar
- 5.Guo Y, Zhao Y, Lu Z, Liu J (2008) The design of improved fuzzy controller based on MCU for central air conditioner. In: International symposium on intelligent information technology application workshops, IEEE Press, New York, 2008, pp 197–200Google Scholar