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Cruise control systems in cars are designed as multi-input systems to maintain a driver's desired speed while compensating for external disturbances such as changes in terrain. The block diagram for a cruise control system typically includes two main inputs: the desired speed set by the driver and any external disturbances, such as the incline of the road. By adjusting the engine throttle, the system maintains the vehicle's speed as close to the desired value as possible.
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Controller configurations are crucial in a car's cruise control system because they manage speed over time to maintain a consistent pace regardless of road conditions, thereby meeting design goals. In traditional control systems, fixed-configuration design involves predetermined controller placement. System performance modifications are known as compensation.
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Related Experiment Video

Updated: Jan 13, 2026

Optimization, Test and Diagnostics of Miniaturized Hall Thrusters
12:22

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Published on: February 16, 2019

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Low computational complexity model predictive control for high-speed trimaran motion reduction.

Zhiyuan Huang1, Jun Zhang1, Zhilin Liu2

  • 1School of Electrical Information Engineering, Jiangsu University, Zhenjiang, 212013, China.

ISA Transactions
|January 8, 2026
PubMed
Summary
This summary is machine-generated.

This study introduces a low-complexity predictive control framework for trimaran motion reduction. The novel method significantly cuts heave and pitch motion, achieving real-time feasibility for enhanced maritime stability.

Keywords:
Computational efficiencyDual-mode MPCHigh-speed trimaranLaguerre functionsMotion reduction

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Area of Science:

  • Marine Engineering
  • Control Systems Engineering
  • Naval Architecture

Background:

  • Model Predictive Control (MPC) faces high computational complexity for trimaran motion reduction.
  • Existing methods struggle with real-time implementation and efficiency in dynamic marine environments.

Purpose of the Study:

  • To develop a computationally efficient predictive control framework for trimaran motion reduction.
  • To ensure stability and effectiveness in challenging sea conditions.

Main Methods:

  • A low-complexity predictive control framework integrating three mechanisms: optimal baseline with auxiliary variables, Laguerre function parameterization for dimension compression, and a double-constraint triggering mechanism for adaptive optimization frequency reduction.
  • Input-to-state stability (ISS) established via Lyapunov theory with terminal constraints.

Main Results:

  • Reduced root-mean-square (RMS) heave displacement by 58.61% and pitch angle by 50.27% under Sea State 4 simulations.
  • Demonstrated real-time feasibility with a computation time of 36 ms for a 100-step horizon, suitable for a 50 ms control cycle.
  • Validated practical effectiveness through experimental tests on a 1:10 scaled trimaran.

Conclusions:

  • The proposed low-complexity predictive control framework effectively reduces trimaran motion with computational efficiency.
  • The method offers a practical solution for real-time motion control in maritime applications.
  • Achieved significant motion reduction and stability, confirming its potential for operational use.