Modified Active Disturbance Rejection Predictive Control: A fixed-order state–space formulation for SISO systems.

This paper presents a novel control strategy that provides active disturbance rejection predictive control on constrained systems with no nominal identified model. The proposed loop relaxes the modelling requirement to a fixed discrete-time state–space realisation of a first-order plus integrator plant despite the nature of the controlled process. A third-order discrete Extended State Observer (ESO) estimates the model mismatch and assumed plant states. Moreover, the constraints handling is tackled by incorporating the compensation term related to the total perturbation in the definition of the optimisation problem constraints. The proposal merges in a new way state–space Model Predictive Control (MPC) and Active Disturbance Rejection Control (ADRC) into an architecture suitable for the servo-regulatory operation of linear and non-linear systems, as shown through validation examples. • Active disturbance rejection is merged with state–space model predictive control. • System information is relaxed to a second-order general integral assumed plant. • The compensation term is used to reformulate the optimisation problem constraints. • Suitable for linear and nonlinear benchmarks with no nominal model. • System constraints are satisfied, and disturbance rejection is enhanced. [ABSTRACT FROM AUTHOR]