Consensus tracking control via iterative learning for singular multi‐agent systems

Consensus Control of Multi-agent Robot System with State Delay Based on Fractional-Order Iterative Learning Control Algorithm

“…The consensus control, as a representative problem of the collaborative control of the multi-agent robot system, aims to design a suitable control algorithm to regulate the state or output of each robot in a finite time. The coordination and consensus between multiple agents have attracted much attention from the academia, yielding fruitful results [3][4][5][6]. However, most consensus control methods for multiple agents are based on integer-order descriptions of the agents, that is, the differential equations of the robots are of integer-order [7,8].…”

Iterative learning control for semi‐linear distributed parameter systems based on sensor–actuator networks

“…[10] first proposed the ILC in the year 1984 to obtain a better operation of robots. At present, ILC has become a vibrant research field of control theory [11–14] and is applied in a number of practical applications, such as piezoelectric actuator [15], flexible manipulator [16], batch processes [17, 18] and urban road networks [19]. It plays an important role in the DPS when its operations are repetitive processes.…”

Consensus Tracking Via Iterative Learning Control for Singular Fractional-Order Multi-Agent Systems Under Iteration-Varying Topologies and Initial State Errors

“…Iterative learning control (ILC) has been widely utilized to cope with the repeated tracking control with high precision requirement in the fixed time interval due to its simplicity and effectiveness [8], [9]. Hence, ILC has been successfully implemented to many kinds of multi-agent systems in recent references, such as high-order nonlinear MASs [10], singular MASs [11], fractional-order MASs [12], and distributed parameter MASs [13]- [15], etc.. In [16], [17], the formation control problems of nonlinear MASs under switching interaction topologies were addressed by employing the ILC scheme.…”

“…It should be pointed out that all the aforementioned published works achieve consensus task after a finite time [28]. To accomplish the consensus task over a fixed time interval, the unified D-type iterative learning algorithm was firstly designed for a class of linear singular MASs in both continuous-time and discrete-time domain to ensure the outputs of followers converge to the leader's trajectory [11]. As is well known, fractional calculus has a long history which can be dated back to the 17th century, many researchers from physics, engineering and biology observe that a fruit number of systems can be modelled by fractional-order differential equations, such as, battery behavior, electromagnetic systems, etc.…”