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Summary: In this paper, we propose an iterative learning control strategy to track a desired trajectory for a class of uncertain systems governed by nonlinear differential inclusions. By imposing Lipschitz continuous condition on a set‐valued mapping described by a closure of the convex hull of a set and using D‐type and PD‐type updating laws with initial iterative learning, we establish the iterative learning process and give a new convergence analysis with the help of Steiner‐type selector. Finally, numerical examples are provided to verify the effectiveness of the proposed method with suitable selection of set‐valued mappings. An application to the speed control of robotic fish is also given. [ABSTRACT FROM AUTHOR]

Abstract In this paper, we present a numerical solution for a finite time complete tracking problem based on the iterative learning control technique for dynamical systems governed by partial differential inclusions of parabolic type with noninstantaneous impulses. By imposing a standard Lipschitz condition on a set-valued mapping and applying conventional P-type updating laws with an initial iterative learning mechanism, we successfully establish an iterative learning process for the tracking problem and conduct a novel convergence analysis with the help of Steiner-type selectors. Sufficient conditions are presented for ensuring asymptotical convergence of the tracking error to zero. Numerical examples are provided to verify the effectiveness of the proposed method with a suitable selection of set-valued mappings. [ABSTRACT FROM AUTHOR]

In this paper, we utilize fractional calculus, theory of semigroup and fixed point approach to prove existence and approximate controllability results for a class of fractional differential equations (FDEs) with noninstantaneous impulses by constructing a suitable composite control function, imposing that the associated linear problem is approximately controllable on the terminal subinterval and dividing our global task into many subtasks on each subinterval. Next, we apply P-type iterative learning control (ILC) updating law to generate a sequence of control functions to find a desired control function to guarantee the error between the output and the desired reference trajectories tending to zero via a suitable norm in the sense of uniform convergence. As a result, the limit of the sequence of control functions is the required control to guarantee the above problem is approximately controllable. In addition, a numerical example is illustrated to demonstrate ILC scheme to solve approximate controllability of time fractional impulsive PDEs via tracking the given continuous and discontinuous trajectory. [ABSTRACT FROM AUTHOR]

An important issue in the area of multi-operation systems is the observation of a discontinuous trajectory. In order to track a discontinuous output trajectory, we choose impulsive differential systems to generate a series of local continuous state trajectories, which become a set of output trajectories via the action of the output functions. Concerning impulsive differential control systems, we design proportional–derivative (PD-type) and proportional plus one order derivative and fractional order derivative (PDDα-type) iterative learning control laws with initial state learning. In particular, the PDDα-type law is more flexible due to the impact of a certain fractional order factor α. Thereafter, we give the associated convergence characteristics by establishing sufficient conditions on open-loop and closed-loop iterative learning schemes in the sense of λ-norm under mild assumptions. Finally, several numerical examples, including an application to robotic fish, are given to illustrate our results. [ABSTRACT FROM AUTHOR]