Fuzzy Finite-Time Command Filtering Output Feedback Control of Nonlinear Systems

Finite‐time adaptive fuzzy command filtering control for stochastic nonlinear systems with input quantization

“…It is assumed that 𝜒 1 ≠ 0 as in Reference 62. On the of Theorem 1, the virtual control law in (30), the actual control input in (54) and the adaptive law ̇Θ in (58). The simulation is implemented with the system parameters C = 0.01, D = 0.01, the initial value [𝜒 1 (0), 𝜒 2 (0), Θ(0)] T = [1, 2.5, 0.1] T , and the controller parameters k 1 = 3, k 2 = 10, h 1 = 1, h 2 = 5, 𝜂 = 0.1, 𝜇 = 0.3, 𝛾 = 0.9999, 𝜔 𝜋 = 80, 𝜍 = 0.85, 𝛿 = 0.5, u min = 0.2.…”

“…Recently, the interest in adaptive control of nonlinear systems is growing rapidly, and many promising schemes have been reported. [21][22][23][24][25][26][27][28][29][30][31][32][33][34][35][36][37] There are a lot of remarkable results in the study of adaptive control schemes for nonlinear systems with quantized control signals, such as. [38][39][40][41][42][43][44][45][46][47][48] In Reference 38, the issue of finite-time tracking control was discussed for nonlinear quantized systems with unmeasurable states.…”

Adaptive fixed‐time fuzzy control for nonlinear systems with actuator faults

“…Because of its advantages of fast convergence rate, strong disturbance rejection and high control accuracy, finite time control has been widely concerned and a large of promising achievements have been developed. [29][30][31][32][33][34][35][36][37] All of these researches are the traditional finite time control method which the setting time function is affected by the initial state of the system. It is obviously that the traditional finite time control is difficult to apply to practical engineering, because not every practical system can obtain the initial state in advance.…”

“…Finite time control is necessary for practical engineering control which can ensure the controlled systems normally reach steady response from transient response quickly. Because of its advantages of fast convergence rate, strong disturbance rejection and high control accuracy, finite time control has been widely concerned and a large of promising achievements have been developed 29‐37 . All of these researches are the traditional finite time control method which the setting time function is affected by the initial state of the system.…”

Fixed‐time self‐structuring neural network cooperative tracking control of multi‐robot systems with actuator faults

“…A large number of valuable research achievements have emerged. [1][2][3] The research directions mainly focus on asymptotic convergence, finite-time convergence and fixed-time convergence. Research results on asymptotic convergence 4,5 are the most abundant.…”