The increasingly more aggressive global competition for the production of higher-quality products at lower costs, along with a general trend away from new capital investments in the U.S., has placed considerable pressure on the process engineers to operate the existing plants more efficiently and to use the same plant for the production of many different products. The more efficient operation has been realized by better process control and monitoring while available product-quality and composition sensors have been inadequate. In many processes, although product quality cannot be measured readily, it can be estimaterd/inferred in real time from the readily available measurements, allowing for inferential control of the product quality. This paper presents a survey of several contemporary methods of state and parameter estimation and their applications in inferential control and adaptive control. The limits and abilities of the methods, the present status of the technological applications, and the need for future advances in the theory, hardware, software, and knowledge transfer will be discussed. Throughout the paper, several examples will be given to illustrate some of the methods surveyed.