Design and experimental evaluation of a predictive PID controller
Takuya Kinoshita, Shin Wakitani, Toru Yamamoto
Abstract
Takuya Kinoshita, Shin Wakitani, Toru Yamamoto
Abstract
PID control schemes have been widely used in most process industries. Since the control performance strongly depends on PID parameters, it is important to suitably choose a set of these parameters. Especially, it is difficult to determine these parameters in the case where the time-delay is unknown and/or large. On the other hand, it is well-known that the generalized predictive control(GPC) design method effectively works for such systems. Then, a new PID tuning scheme(GPC-PID) which is derived from the relationship between the GPC and the PID control laws is explained in this paper. The GPC-PID controller has a user-specified parameter, and it is adjusted from the viewpoint of the robust stability. The effectiveness of the GPC-PID controller is verified by application to a temperature control system whose time-delay can be changed to test the control scheme.
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PID control schemes have been widely used in most process industries. Since the control performance strongly depends on PID parameters, it is important to suitably choose a set of these parameters. Especially, it is difficult to determine these parameters in the case where the time-delay is unknown and/or large. On the other hand, it is well-known that the generalized predictive control(GPC) design method effectively works for such systems. Then, a new PID tuning scheme(GPC-PID) which is derived from the relationship between the GPC and the PID control laws is explained in this paper. The GPC-PID controller has a user-specified parameter, and it is adjusted from the viewpoint of the robust stability. The effectiveness of the GPC-PID controller is verified by application to a temperature control system whose time-delay can be changed to test the control scheme.
Key concepts: PID controller, Control theory (sociology), Model predictive control, Process control, Computer science, Stability (learning theory), Process (computing), Control engineering