Stochastic self-triggered MPC for linear constrained systems under additive uncertainty and chance constraints

Self-Triggered Stochastic MPC for Linear Systems With Disturbances

“…. , v * mj −1|kj } are transmitted to the actuator through the communication network (see [9], [17], [18]).…”

“…Interested readers are referred to [13]- [15] and also to [12] and [16] for an overview of SMPC. Note that the studies on event-based SMPC schemes are limited and, to the best of our knowledge, are reported only in the most recent works [17], [18], in which the robust self-triggering approach in [9] is extended to a stochastic setting. This triggering strategy might not necessarily relieve the communication load from the controller side, since a control sequence is required to be transmitted through the network at each triggering instant, while the load of transmitting m different data together at once is not less than transmitting one data a time for m times [11].…”

Self-Triggered Adaptive Model Predictive Control of Constrained Nonlinear Systems: A Min-Max Approach

“…Estimate Xj+1 and Vj+1 by using (10) and (11), respectively. Compute L t k by using (12), then Vt k can be obtained by following (13). 7: else 8:…”

“…To enlarge the region of attraction, the integration of self-triggered MPC with homothetic tubes is proposed in [17], where the state tubes are optimized online to reduce the conservatism. The probabilistic constraints and stochastic disturbances are considered in [12], [18]. For nonlinear systems, in [11] a robust self-triggered MPC scheme is developed for unconstrained nonlinear affine systems, where the triggering interval is maximized by comparing the current optimal cost and the predicted optimal cost.…”

Self‐triggered adaptive prescribed‐time tracking control for stochastic nonlinear systems

“…It should be pointed out that when the measurement error meets the pre‐defined threshold condition, the control signal will be updated immediately and will be applicable to the control system, which means that the system states need to be continuously monitored. Considering the feasibility of actual physical implementation, a self‐triggered (ST) control method 11‐13 has been widely concerned because of its outstanding advantage in eliminating the need for continuous supervision, that is, this control method is only based on the current state measurement, and the next sampling time can be scheduled at the current time. In Reference 11, a stochastic self‐triggered control approach was put forward for linear system with probabilistic constraints to reduce the amount of controller update so as to effectively reduce the use of communication resources.…”