Minimax approaches to robust model predictive control

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MIN-MAX MODEL PREDICTIVE CONTROL AS A QUADRATIC PROGRAM (2005, background): “The control input is given by uk = Kxk + vk, where K is chosen in order to achieve some desired property for the non constrained problem such as stability or LQR optimality (see (Bemporad, 1998; Alamo et al., 2003; Löfberg, 2003)).”
Stochastic Model Predictive Control: An Overview and Perspectives for Future Research (2016, unknown): “Inspired by [16], [74], and [75], an SMPC approach is presented in [47] for linear systems with Gaussian additive disturbances [see (7a)], where the feedback control law ( ) i $ r is defined in terms of an affine function of past disturbances”
Ship Collision Avoidance and COLREGS Compliance Using Simulation-Based Control Behavior Selection With Predictive Hazard Assessment (2016, unknown): “I. INTRODUCTION”
Optimization over state feedback policies for robust control with constraints (2006, background): “tive control with Gaussian state disturbances [55,56] and bounded state disturbances [40, 41 ].”
Predictive Control for Linear and Hybrid Systems (2017, methodology): “74) The following result has been proven in [130], the convexity property has also appeared in [194][Section 7.”
Output feedback model predictive control of uncertain norm‐bounded linear systems (2011, background): “A similar approach was developed in [9] for nominal linear discrete-time plants, under the assumption of unknown but bounded measurement errors.”