"Internal model control. 4. PID controller design." Reply to comments

1987 ◽  
Vol 26 (10) ◽  
pp. 2163-2163 ◽  
Author(s):  
Manfred Morari ◽  
Peter Campo
Keyword(s):  
Pid Controller ◽  
Internal Model ◽  
Controller Design ◽  
Internal Model Control ◽  
Model Control ◽  
Pid Controller Design

Internal model control: PID controller design

1986 ◽  
Vol 25 (1) ◽  
pp. 252-265 ◽  
Author(s):  
Daniel E. Rivera ◽  
Manfred Morari ◽  
Sigurd Skogestad
Keyword(s):  
Pid Controller ◽  
Internal Model ◽  
Controller Design ◽  
Internal Model Control ◽  
Model Control ◽  
Pid Controller Design

FPGA Based Modified Fuzzy PID Controller for Pitch Angle of Bench-top Helicopter

2012 ◽  
Vol 8 (8) ◽  
pp. 12-24
Author(s):  
Ammar Aldair
Keyword(s):  
Pid Controller ◽  
Controller Design ◽  
Simulation Software ◽  
Internal Model Control ◽  
Rule Base ◽  
Plant Responses ◽  
Fuzzy Pid ◽  
Fuzzy Pid Controller ◽  
Model Control ◽  
Pid Controller Design

Fuzzy PID controller design is still a complex task due to the involvement of a large number of parameters in defining the fuzzy rule base. To reduce the huge number of fuzzy rules required in the normal design for fuzzy PID controller, the fuzzy PID controller is represented as Proportional-Derivative Fuzzy (PDF) controller and Proportional-Integral Fuzzy (PIF) controller connected in parallel through a summer. The PIF controller design has been simplified by replacing the PIF controller by PDF controller with accumulating output. In this paper, the modified Fuzzy PID controller design for bench-top helicopter has been presented. The proposed Fuzzy PID controller has been described using Very High Speed Integrated Circuit Hardware Description Language (VHDL) and implemented using the Field Programmable Gate Array (FPGA) board. The bench-top helicopter has been used to test the proposed controller. The results have been compared with the conventional PID controller and Internal Model Control Tuned PID (IMC-PID) Controller. Simulation results show that the modified Fuzzy PID controller produces superior control performance than the other two controllers in handling the nonlinearity of the helicopter system. The output signal from the FPGA board is compared with the output of the modified Fuzzy PID controller to show that the FPGA board works like the Fuzzy PID controller. The result shows that the plant responses with the FPGA board are much similar to the plant responses when using simulation software based controller.

Robust Controllers for Pulse-Width-Modulated D.C./D.C. Converters Using Internal-Model-Control Design

1993 ◽  
Vol 207 (3) ◽  
pp. 127-134 ◽  
Author(s):  
D Garabandić ◽  
T Petrović
Keyword(s):  
Model Uncertainty ◽  
Pulse Width ◽  
Internal Model ◽  
Controller Design ◽  
Optimization Method ◽  
Internal Model Control ◽  
Linear Feedback ◽  
Pulse Width Modulated ◽  
Linear Feedback Controller ◽  
Model Control

A linear feedback controller for pulse-width-modulated d.c./d.c. regulator is designed using a frequency domain optimization method based on internal-model-control theory. This method aims to produce suboptimal low-order controllers which are ‘robust’, in the sense that the closed-loop system is guaranteed to meet stability objectives in the presence of model uncertainty. The small-signal model of a d.c./d.c. converter is used for the controller design. The model uncertainty description derived here is based on experiments and non-linear modelling. The result of the synthesis is a family of controllers, and each member of this family satisfies the robust control objectives. All controllers have a multi-loop structure including two feedback loops and one feedforward loop. A detailed design of the controller, including experimental results, is presented.

Multiloop FOPID Controller Design for TITO Process Using Evolutionary Algorithm

2019 ◽  
Vol 8 (3) ◽  
pp. 117-130 ◽  
Author(s):  
Lakshmanaprabu S.K. ◽  
Najumnissa Jamal D. ◽  
Sabura Banu U.
Keyword(s):  
Evolutionary Algorithm ◽  
Pid Controller ◽  
Controller Design ◽  
Search Algorithm ◽  
Bat Algorithm ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Internal Model Control ◽  
Model Control ◽  
Fractional Order Pid

In this article, the tuning of multiloop Fractional Order PID (FOPID) controller is designed for Two Input Two Output (TITO) processes using an evolutionary algorithm such as the Genetic algorithm (GA), the Cuckoo Search algorithm (CS) and the Bat Algorithm (BA). The control parameters of FOPID are obtained using GA, CS, and BA for minimizing the integral error criteria. The main objective of this article is to compare the performance of the GA, CS, and BA for the multiloop FOPID controller problem. The integer order internal model control based PID (IMC-PID) controller is designed using the GA and the performance of the IMC-PID controller is compared with the FOPID controller scheme. The simulation results confirm that BA offers optimal controller parameter with a minimum value of IAE, ISE, ITAE with faster settling time.

Robust and Effective PID Controller Identification for Delay Dominant Systems

2014 ◽  
Vol 625 ◽  
pp. 478-481
Author(s):  
Lemma Dendena Tufa ◽  
Marappagounder Ramasamy
Keyword(s):  
Time Delay ◽  
Time Constant ◽  
Pid Controller ◽  
Internal Model ◽  
Control Structure ◽  
Internal Model Control ◽  
Controller Tuning ◽  
Model Control ◽  
Pid Controller Tuning ◽  
Improved Performance

A novel PID controller identification method based on internal model control structure is proposed. The proposed method avoids the necessity of approximating the time delay for designing the PID controller. It results in a robust and effective PID controller tuning. The method is effective for both time constant and time delay dominant systems, with much improved performance for the latter case.

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