Predictive controller design for networked systems

This thesis considered the analysis and design of networked control systems with the communication delay and data loss, which are responsible for degradation of the control performance. Predictive control strategy is applied to compensate the communication delay and data loss in the NCS. The stability and the system performance of the close-loop networked control system are analyzed. Also, this control strategy is applied to a DC servo control system with communication delay and data packet loss. The stability of the closed-loop networked predictive control system has been analyzed and the comparison with other existing networked control methods like H_∞ control [20] , Networked predictive control for random network delays in both forward and feedback channels [21] and Model-based control [22]

Design and Stability Analysis of Uncertain Networked Predictive Control Systems with Multiple Forward Channels

This paper is concerned with the design and stability of networked predictive control for uncertain systems with multiple forward channels. The delays and packet dropouts are distributed such that the classic networked predictive control (NPC) needs modifications to be implemented. An improved control signal selection scheme with distributed prediction length is proposed to increase the prediction accuracy and hence achieve better control performance. Moreover, stability analysis results are obtained for both constant and random cases. Interestingly, it is shown that the stability of the closed-loop NPC system is not related to the distributed delays when they are constant and the system model is accurate. Finally, a two-axis milling machine example is given to illustrate the effectiveness of the proposed method

Model predictive controllers for a networked DC servo system

Feedback control systems, wherein the loops used to control the behavior of a plant are closed through a real time communication network, are called networked control systems. Networked Control Systems (NCSs) are one type of distributed control systems where sensors, actuators, and controllers are interconnected by communication networks. The primary advantages of an NCS are reduced system wiring, ease of system analysis and maintenance. In this thesis, the analysis and design of networked control systems with the communication delay and data loss, which are responsible for degradation of the control performance, are considered. Model predictive control strategies are applied to compensate the communication delay and data loss in the NCS. Studied about TrueTime Simulator and the control strategies are applied to a DC servo system using this TrueTime Simulator with communication delay and data packet loss. Also, the stability and the system performance of the close loop networked control system are analyzed

Robust model predictive control under redundant channel transmission with applications in networked DC motor systems

In networked systems, intermittent failures in data transmission are usually inevitable due to the limited bandwidth of the communication channel, and an effective countermeasure is to add redundance so as to improve the reliability of the communication service. This paper is concerned with the model predictive control (MPC) problem by using static output feedback for a class of polytopic uncertain systems with redundant channels under both input and output constraints. By utilizing the min-max control approach combined with stochastic analysis, sufficient conditions are established to guarantee the feasibility of the designed MPC scheme that ensures the robust stability of the closed-loop system. In terms of the solution to an auxiliary optimization problem, an easy-to-implement MPC algorithm is proposed to obtain the desired sub-optimal control sequence as well as the upper bound of the quadratic cost function. Finally, to illustrate its effectiveness, the proposed design method is applied to control a networked direct current motor system

Time Delay Compensation and Stability Analysis of Networked Predictive Control Systems Based on Hammerstein Model

A novel approach is proposed for a networked control system with random delays containing a nonlinear process based on a Hammerstein model. The method uses a time delay two step generalized predictive control (TDTSGPC), which consists of two parts, one is to deal with the input nonlinearity of the Hammerstein model and the other is to compensate the network induced delays in the networked control system. Theoretical results using the Popov theorem are presented for the closed-loop stability of the system in the case of a constant delay. Simulation examples illustrating the validity of the approach are presented

H∞ controller design for networked predictive control systems based on the average dwell-time approach

This brief focuses on the problem of H∞ control for a class of networked control systems with time-varying delay in both forward and backward channels. Based on the average dwell-time method, a novel delay-compensation strategy is proposed by appropriately assigning the subsystem or designing the switching signals. Combined with this strategy, an improved predictive controller design approach in which the controller gain varies with the delay is presented to guarantee that the closed-loop system is exponentially stable with an H∞-norm bound for a class of switching signal in terms of nonlinear matrix inequalities. Furthermore, an iterative algorithm is presented to solve these nonlinear matrix inequalities to obtain a suboptimal minimum disturbance attenuation level. A numerical example illustrates the effectiveness of the proposed method

Sparse Packetized Predictive Control for Networked Control over Erasure Channels

We study feedback control over erasure channels with packet-dropouts. To achieve robustness with respect to packet-dropouts, the controller transmits data packets containing plant input predictions, which minimize a finite horizon cost function. To reduce the data size of packets, we propose to adopt sparsity-promoting optimizations, namely, ell-1-ell-2 and ell-2-constrained ell-0 optimizations, for which efficient algorithms exist. We derive sufficient conditions on design parameters, which guarantee (practical) stability of the resulting feedback control systems when the number of consecutive packet-dropouts is bounded.Comment: IEEE Transactions on Automatic Control, Volume 59 (2014), Issue 7 (July) (to appear

Packetized Predictive Control for Rate-Limited Networks via Sparse Representation

We study a networked control architecture for linear time-invariant plants in which an unreliable data-rate limited network is placed between the controller and the plant input. The distinguishing aspect of the situation at hand is that an unreliable data-rate limited network is placed between controller and the plant input. To achieve robustness with respect to dropouts, the controller transmits data packets containing plant input predictions, which minimize a finite horizon cost function. In our formulation, we design sparse packets for rate-limited networks, by adopting an an ell-0 optimization, which can be effectively solved by an orthogonal matching pursuit method. Our formulation ensures asymptotic stability of the control loop in the presence of bounded packet dropouts. Simulation results indicate that the proposed controller provides sparse control packets, thereby giving bit-rate reductions for the case of memoryless scalar coding schemes when compared to the use of, more common, quadratic cost functions, as in linear quadratic (LQ) control.Comment: 9 pages, 7 figures. arXiv admin note: text overlap with arXiv:1307.824