In this paper we present an approach to test stability and feasibility of discrete-time LTI systems subject to constrained optimal control. The analysis is based on the feedback solution of the constrained optimal control problem formulated in a Receding Horizon fashion. The validation procedure consists of two independent parts. For stability, a piecewise quadratic Lyapunov function is compute...

This paper presents a data-driven receding horizon fault estimation method for additive actuator and sensor faults in unknown linear time-invariant systems, with enhanced robustness to stochastic identification errors. State-of-the-art methods construct fault estimators with identified state-space models or Markov parameters, but they do not compensate for identification errors. Motivated by th...

An infinite horizon controller is developed that allows incorporation of input and state constraints in a receding horizon feedback strategy. For both stable and unstable linear plants, feasibility of the constraints guarantees nominal closed-loop stability for all choices of the tuning parameters in the control law. The constraints’ feasibility Manuscript received September 20, 1991; revised M...

Model-Error Control Synthesis employs an optimal real-time nonlinear estimator to determine model error corrections to a nominal controller. Control compensation is achieved by using the estimated model error as a signal synthesis adaptive correction to the nominal control input so that maximum performance is achieved in the face of extreme model uncertainty and disturbance inputs. In this pape...