STABILITY AND PERFORMANCE OF NETWORKED CONTROL SYSTEMS

Network control systems (NCSs), as one of the most active research areas, are arousing comprehensive concerns along with the rapid development of network. This dissertation mainly discusses the stability and performance of NCSs into the following two parts. In the first part, a new approach is proposed to reduce the data transmitted in networked control systems (NCSs) via model reduction method. Up to our best knowledge, we are the first to propose this new approach in the scientific and engineering society. The "unimportant" information of system states vector is truncated by balanced truncation method (BTM) before sending to the networked controller via network based on the balance property of the remote controlled plant controllability and observability. Then, the exponential stability condition of the truncated NCSs is derived via linear matrix inequality (LMI) forms. This method of data truncation can usually reduce the time delay and further improve the performance of the NCSs. In addition, all the above results are extended to the switched NCSs. The second part presents a new robust sliding mode control (SMC) method for general uncertain time-varying delay stochastic systems with structural uncertainties and the Brownian noise (Wiener process). The key features of the proposed method are to apply singular value decomposition (SVD) to all structural uncertainties, to introduce adjustable parameters for control design along with the SMC method, and new Lyapunov-type functional. Then, a less-conservative condition for robust stability and a new robust controller for the general uncertain stochastic systems are derived via linear matrix inequality (LMI) forms. The system states are able to reach the SMC switching surface as guaranteed in probability 1 by the proposed control rule. Furthermore, the novel Lyapunov-type functional for the uncertain stochastic systems is used to design a new robust control for the general case where the derivative of time-varying delay can be any bounded value (e.g., greater than one). It is theoretically proved that the conservatism of the proposed method is less than the previous methods. All theoretical proofs are presented in the dissertation. The simulations validate the correctness of the theoretical results and have better performance than the existing results

Estimation and control with limited information and unreliable feedback

Advancement in sensing technology is introducing new sensors that can provide information that was not available before. This creates many opportunities for the development of new control systems. However, the measurements provided by these sensors may not follow the classical assumptions from the control literature. As a result, standard control tools fail to maximize the performance in control systems utilizing these new sensors. In this work we formulate new assumptions on the measurements applicable to new sensing capabilities, and develop and analyze control tools that perform better than the standard tools under these assumptions. Specifically, we make the assumption that the measurements are quantized. This assumption is applicable, for example, to low resolution sensors, remote sensing using limited bandwidth communication links, and vision-based control. We also make the assumption that some of the measurements may be faulty. This assumption is applicable to advanced sensors such as GPS and video surveillance, as well as to remote sensing using unreliable communication links. The first tool that we develop is a dynamic quantization scheme that makes a control system stable to any bounded disturbance using the minimum number of quantization regions. Both full state feedback and output feedback are considered, as well as nonlinear systems. We further show that our approach remains stable under modeling errors and delays. The main analysis tool we use for proving these results is the nonlinear input-to-state stability property. The second tool that we analyze is the Minimum Sum of Distances estimator that is robust to faulty measurements. We prove that this robustness is maintained when the measurements are also corrupted by noise, and that the estimate is stable with respect to such noise. We also develop an algorithm to compute the maximum number of faulty measurements that this estimator is robust to. The last tool we consider is motivated by vision-based control systems. We use a nonlinear optimization that is taking place over both the model parameters and the state of the plant in order to estimate these quantities. Using the example of an automatic landing controller, we demonstrate the improvement in performance attainable with such a tool

1-Bit processing based model predictive control for fractionated satellite missions

In this thesis, a 1-bit processing based Model Predictive Control (OBMPC) structure is proposed for a fractionated satellite attitude control mission. Despite the appealing advantages of the MPC algorithm towards constrained MIMO control applications, implementing the MPC algorithm onboard a small satellite is certainly challenging due to the limited onboard resources. The proposed design is based on the 1-bit processing concept, which takes advantage of the affine relation between the 1-bit state feedback and multi-bit parameters to implement a multiplier free MPC controller. As multipliers are the major power consumer in online optimization, the OBMPC structure is proven to be more efficient in comparison to the conventional MPC implementation in term of power and circuit complexity. The system is in digital control nature, affected by quantization noise introduced by Δ∑ modulators. The stability issues and practical design criteria are also discussed in this work. Some other aspects are considered in this work to complete the control system. Firstly, the implementation of the OBMPC system relies on the 1-bit state feedbacks. Hence, 1-bit sensing components are needed to implement the OBMPC system. While the ∆∑ modulator based Microelectromechanical systems (MEMS) gyroscope is considered in this work, it is possible to implement this concept into other sensing components. Secondly, as the proposed attitude mission is based on the wireless inter-satellite link (ISL), a state estimator is required. However, conventional state estimators will once again introduce multi-bit signals, and compromise the simple, direct implementation of the OBMPC controller. Therefore, the 1-bit state estimator is also designed in this work to satisfy the requirements of the proposed fractionated attitude control mission. The simulation for the OBMPC is based on a 2U CubeSat model in a fractionated satellite structure, in which the payload and actuators are separated from the controller and controlled via the ISL. Matlab simulations and FPGA implementation based performance analysis shows that the OBMPC is feasible for fractionated satellite missions and is advantageous over the conventional MPC controllers

1-Bit processing based model predictive control for fractionated satellite missions

In this thesis, a 1-bit processing based Model Predictive Control (OBMPC) structure is proposed for a fractionated satellite attitude control mission. Despite the appealing advantages of the MPC algorithm towards constrained MIMO control applications, implementing the MPC algorithm onboard a small satellite is certainly challenging due to the limited onboard resources. The proposed design is based on the 1-bit processing concept, which takes advantage of the affine relation between the 1-bit state feedback and multi-bit parameters to implement a multiplier free MPC controller. As multipliers are the major power consumer in online optimization, the OBMPC structure is proven to be more efficient in comparison to the conventional MPC implementation in term of power and circuit complexity. The system is in digital control nature, affected by quantization noise introduced by Δ∑ modulators. The stability issues and practical design criteria are also discussed in this work. Some other aspects are considered in this work to complete the control system. Firstly, the implementation of the OBMPC system relies on the 1-bit state feedbacks. Hence, 1-bit sensing components are needed to implement the OBMPC system. While the ∆∑ modulator based Microelectromechanical systems (MEMS) gyroscope is considered in this work, it is possible to implement this concept into other sensing components. Secondly, as the proposed attitude mission is based on the wireless inter-satellite link (ISL), a state estimator is required. However, conventional state estimators will once again introduce multi-bit signals, and compromise the simple, direct implementation of the OBMPC controller. Therefore, the 1-bit state estimator is also designed in this work to satisfy the requirements of the proposed fractionated attitude control mission. The simulation for the OBMPC is based on a 2U CubeSat model in a fractionated satellite structure, in which the payload and actuators are separated from the controller and controlled via the ISL. Matlab simulations and FPGA implementation based performance analysis shows that the OBMPC is feasible for fractionated satellite missions and is advantageous over the conventional MPC controllers

Access Scheduling and Controller Design in Networked Control Systems

A Networked Control System (NCS) is a control system in which the sensors and actuators are connected to a feedback controller via a shared communication medium. In an NCS, the shared medium can only provide a limited number of simultaneous connections for the sensors and actuators to communicate with the controller. As a consequence, the design of an NCS involves not only the specification of a feedback controller but also that of a communication policy that schedules access to the shared communication medium. Up to now, this task has posed a significant challenge, due in large part to the modeling complexity of existing NCS architectures, under which the control and communication design problems are tightly intertwined. This thesis proposes an alternative NCS architecture, whereby the plant and controller choose to ``ignore'' the actuators and sensors that are not actively communicating. This new architecture leads to simpler NCS models in which the design of feedback controller and communication polices can be effectively decoupled. In that setting, we propose a set of medium access scheduling strategies and accompanying controller design methods that address a broad range of stabilization, estimation, and optimization problems for a general class of NCSs. The performance of the proposed methods is illustrated through a set of simulations and hardware experiments