GP-based Offset-free MPC using Disturbance Models and MHE

Data-driven stochastic model predictive control for spacecraft attitude tracking

Koopman-based model predictive control for nonlinear systems with bounded model uncertainty

Model Predictive Control for MIMO Systems Integrated with Active Disturbance Rejection

This paper presents a proposal for a novel predictive control scheme for uncertain and disturbed multi-input, multi-output (MIMO) systems. The proposed method is a fusion of a well-known and effective linear Model Predictive Control (MPC) and a modern concept, Active Disturbance Rejection Control (ADRC). The approach i...

Gaussian-Process Model Predictive Trajectory Tracking Control for Unmanned Surface Vehicles Under Model Uncertainty

Model uncertainty and environmental disturbances can significantly degrade unmanned surface vehicle (USV) trajectory tracking when only a nominal kinematic model is used. This paper proposes a Gaussian-process model predictive control (GP-MPC) method for USVs under input-dependent disturbances. A three-degree-of-freedo...

ADAPTIVE NEURAL NETWORK-ASSISTED LINEAR QUADRATIC REGULATOR CONTROL WITH FULL-ORDER EXTENDED STATE OBSERVER FOR ACTIVE SUSPENSION SYSTEMS

This paper proposes integrating a Linear Quadratic Regulator (LQR) control scheme with an adaptive Neural Network (NN) updating law to improve ride comfort performance and confirms the effectiveness of the proposed control strategy in suspension system regulation.

Reduced-Order ESO-Based Predictor Control for Time-Delay Processes

This paper proposes a control structure for SISO any-order time-delay processes. The proposed approach combines predictor-based strategies, known for its enhanced state and disturbance prediction capabilities, with a reduced-order extended state observer (ESO). To enhance robustness, a direct relationship is establishe...