Event-Triggered Recursive Filtering for Shift-Varying Linear Repetitive Processes

Observer-Based Bounded H∞ Control for Shift-Varying Linear Repetitive Processes With Constrained Bit Rates Over a Finite Horizon

This technical correspondence examines the issue of observer-based bounded $H_{\infty }$ control for a kind of shift-varying linear repetitive process (LRP) over networks with constrained bit rates in the finite horizon. Unlike the previous researches that address (or avoid) the problem of limited network resources by designing different scheduling protocols, this study focuses on further reducing and optimizing the bandwidth utilization by introducing a bit rate constraint model. Thus, an encoding-decoding mechanism under the constrained bit rates is proposed based on the quantization method. In order to analyze the $H_{\infty }$ performance of the LRP and design an appropriate controller, the LRP is transformed into a shift-varying two-dimensional (2-D) Fornasini-Marchesini model. Sufficient conditions in recursive linear matrix inequalities are proposed to ensure that the extended system achieves a bounded $H_{\infty }$ performance over a finite horizon within the 2-D framework. Furthermore, a component-based strategy for allocating the bit rates is provided to expand the quantization region under the constraint of bit rates. Finally, the effectiveness of the proposed method is verified by a simulation example.

Probability-guaranteed set-membership filtering for nonlinear 2-D systems with measurement outliers under the adaptive event-triggered mechanism

This paper is primarily devoted to investigating the probability-guaranteed set-membership (PGSM) filtering problem for a class of nonlinear two-dimensional (2-D) systems with measurement outliers under the adaptive event-triggered mechanism (AETM). Here, the sensors are connected to the remote filter through a bandwidth-limited communication network. With the purpose of reducing the communication burden, a novel AETM is proposed to optimize the scheduling of transmitted data to the filter, where the triggering threshold is allowed to be dynamically adjusted based on the transmission error. This paper aims to develop a two-step recursive PGSM filter, ensuring that the filtering error remains within the prescribed ellipsoidal set with a specified probability. To safeguard the filtering process against performance degradation caused by measurement outliers, a saturation function is incorporated into the filter structure to restraint the impact of outlier-contaminated innovations. By utilizing the mathematical induction approach and convex optimization technique, a sufficient condition is derived to guarantee the existence of the desired PGSM filter, and the filter gains are obtained in terms of the solutions to a series of convex optimization problems with ellipsoidal constraints. In the end, an illustrative example is implemented to reveal the effectiveness of the addressed filter design scheme. The results demonstrate that, compared with the Kalman filter and set-membership (SM) filter, the proposed PGSM filter exhibits superior filtering performance and low upper bound of filtering error in the presence of unknown but bounded (UBB) noise.

Predictor-Based Periodic Event-Triggered Control for Dual-Rate Networked Control Systems With Disturbances

This article considers the problem of periodic event-triggered control design for dual-rate networked control systems subject to nonvanishing disturbance. The plant considered in this article is a kind of dual-rate networked control system, where the sensor samples the measurement output at a slow rate and the actuator updates the control input at a fast rate. Despite the slow-rate sampling of the sensor, a new output predictor-based observer is proposed to accurately estimate system state and disturbance in the intersample time interval, and an active anti-disturbance controller that updates at a fast rate is accordingly proposed, such that the desirable control performance and disturbance rejection performance can be achieved. At each fast-rate updating time instant, we use the prediction technique to generate a data packet, including the computed current control input and the predicted values of the control inputs for the future finite steps, and design a new periodic event-triggered mechanism to determine whether to transmit the data packet via a communication network or not. The proposed control method is easily implemented in digital platform since it has a discrete-time form. To verify the effectiveness of the proposed control method, we finally present the simulation results of a practical speed control system.