Most previous work about the hardware design of a fuzzy logic controller (FLC) intended to either improve its inference performance for real-time applications or to reduce its hardware cost. To our knowledge, there has been no attempt to design a hardware FLC that can perform an adaptive fuzzy inference for the applications of on-line adaptation. The purpose of this paper is to present such an adaptive memory-efficient FLC and its applications. Taking advantage of the adaptability provided by a symbolic fuzzy rule format and the dynamic membership function generator, as well as the high-speed integration capability afforded by VLSI, the proposed adaptive fuzzy logic controller (AFLC) can perform an adaptive fuzzy inference process using various inference parameters, such as the shape and location of a membership function, dynamically and quickly. Three examples are used to illustrate its applications, and the experimental results show the excellent adaptability provided by AFLC.