Fuzzy-approximation-based decentralized adaptive control for pure-feedback large-scale nonlinear systems with time-delay

Quantized-output-feedback practical prescribed-time design strategy for decentralized tracking of a class of interconnected nonlinear systems with unknown interaction delays

This paper proposes a decentralized practical prescribed-time (PT) tracking design using quantized output feedback (QOF) for uncertain interconnected lower-triangular systems with unknown time-delay interconnections. The local output signals are assumed to be only measured and quantized for the PT tracker design under a band-limited network. By employing a PT-dependent scaling function, a decentralized memoryless PT observer based on quantized local outputs is developed to estimate local unmeasurable state variables. Owing to output quantization, the available output feedback signals become discontinuous. As a result, the tracking error between the actual (i.e., unquantized) local output and the local desired signal cannot be utilized in the local virtual controller. To address this issue, a novel adaptive compensation mechanism is derived to design the local PT neural network tracking laws using only quantized local outputs and estimated states. The proposed PT tracking controller does not require information on the interconnected nonlinear functions and interaction delays. During the Lyapunov stability analysis, the boundary layer error decomposition approach is employed to address the issue of non-differentiability in the local virtual control laws. The proposed QOF control system achieves practical PT stability. It is shown that the settling time of local tracking errors can be predetermined, regardless of the design parameters and initial conditions. Finally, the proposed QOF decentralization strategy is supported with illustrative examples and a comparison to demonstrate its benefits.

Guaranteed cost control via dynamic output feedback for networked interval type-2 T-S fuzzy system with hybrid communication mechanism

This paper aims to investigate the guaranteed cost control via dynamic output feedback for nonlinear networked control systems (NCSs) with consideration of hybrid communication mechanism, data dropout and bounded disturbance. Interval type-2 (IT2) Takagi-Sugeno (T-S) fuzzy model is utilized to describe the nonlinear system with parameter uncertainties. To enhance bandwidth utilization and improve control performance, a hybrid communication mechanism involving both event-triggered mechanism (ETM) and time-triggered mechanism (TTM) is proposed. Two Bernoulli processes are invoked to describe the switching between two triggering mechanisms, and the data dropout phenomenon in communication network, respectively. The quadratic boundedness (QB) technique is employed to specify the closed-loop stability of a bounded disturbance networked system. The sufficient conditions for the stability of the system and the presence of a dynamic output feedback guaranteed cost controller are presented. In addition, the problem of controller design is converted to a convex optimization problem that can be tackled by linear matrix inequalities (LMIs) technique. At last, simulation experiment is carried out to explicate the availability and usefulness of the designed controller.

Minimal-Approximation-Based Decentralized Backstepping Control of Interconnected Time-Delay Systems

A decentralized adaptive backstepping control design using minimal function approximators is proposed for nonlinear large-scale systems with unknown unmatched time-varying delayed interactions and unknown backlash-like hysteresis nonlinearities. Compared with existing decentralized backstepping methods, the contribution of this paper is to design a simple local control law for each subsystem, consisting of an actual control with one adaptive function approximator, without requiring the use of multiple function approximators and regardless of the order of each subsystem. The virtual controllers for each subsystem are used as intermediate signals for designing a local actual control at the last step. For each subsystem, a lumped unknown function including the unknown nonlinear terms and the hysteresis nonlinearities is derived at the last step and is estimated by one function approximator. Thus, the proposed approach only uses one function approximator to implement each local controller, while existing decentralized backstepping control methods require the number of function approximators equal to the order of each subsystem and a calculation of virtual controllers to implement each local actual controller. The stability of the total controlled closed-loop system is analyzed using the Lyapunov stability theorem.