Particle swarm optimization (PSO) is a heuristic global optimization method, proposed
originally by Kennedy and Eberhart in 1995. It is now one of the most commonly used …

This paper presents a comprehensive overview of modelling, simulation and implementation
of neural networks, taking into account that two aims have emerged in this area: the …

Accurate path tracking and stability are the main challenges of lateral motion control in
mobile robots, especially under the situation with complex road conditions. The interaction …

This study proposes a multi-objective sparrow search algorithm (MOSSA) based on a 2k
crowding-distance entropy and the optimal strategy of the positions to solve complex multi …

Multi-objective optimization has been adopted in many engineering problems where a set of
requirements must be met to generate successful applications. Among them, there are the …

This article presents a tracking control design for two-link robot manipulators. To achieve
robust tracking control performance, a super-twisting sliding mode control (STSMC) is …

Artificial potential field has long been proposed in the field of robot path planning. But the
well-known drawbacks like local minimal problem and low efficiency prevent its wide …

This paper presents a novel robust fuzzy adaptive integral sliding mode controller designed
via a multi-objective grey wolf optimization algorithm for a nonlinear uncertain chaotic …

A framework for neural networks (NN) based consensus control is proposed for multiple
robotic manipulators systems (MRMS) under leader–follower communication topology. Two …

With the complexity of multi-objective optimization scenarios, both convergence and
diversity of optimization algorithms are put forward higher requirements, but the harmony …