Salp Swarm Algorithm (SSA) is a novel optimization algorithm which is widely used in engineering problems. An improved SSA inspired by quantum computing is proposed in this paper. The principles of quantum computing, such as qubits and quantum states, are introduced into the original SSA in order to overcome the defect of trapping into local optimum easily. Instead of updating the salp position directly, the quantum angle related to the quantum state is updated to increase the diversity of states. Two multidimensional benchmark functions are used to verify the proposed improved SSA, the result shows that the introduction of quantum computing can successfully prevent the SSA from falling into the local optimum and increase the accuracy.
Fixed-time convergence control strategies based on adaptive Non-Singular Terminal Sliding Mode are proposed for rigid spacecraft attitude stabilization subject to actuator faults. A novel fixed-time sliding mode surface is used. Then, a fixed-time controller with adaptive law is derived to guarantee that the closed-loop system is stable in the sense of the fixed-time concept. Finally, the Lyapunov stability analysis shows that the controller has a good fault-tolerant performance on actuator faults. Numerical simulation verified the good performance of the controller in the attitude stabilization control.
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