The paper introduces a novel quantum algorithm, the Counterdiabatic Feedback-Based Quantum Algorithm (CD-FQA), which integrates quantum Lyapunov control (QLC) with the counterdiabatic driving protocol. This approach aims to enhance the efficiency of preparing ground states in quantum many-body systems and solving combinatorial optimization problems. The CD-FQA algorithm is designed to accelerate population transfer to low-energy states compared to conventional feedback-based quantum algorithms, reducing the quantum circuit depth and computational resources required. The authors apply the CD-FQA to one-dimensional quantum Ising spin chains, demonstrating its effectiveness through comprehensive simulations. The algorithm's performance is compared with the standard Feedback-Based Quantum Algorithm (FQA) and classical simulations. The results show that the CD-FQA significantly reduces the time needed to reach low-energy states, with the best performance achieved using the $Y$ operator as the second control Hamiltonian. The study also explores the impact of various parameters, such as the control field strength $\alpha$, system size $N$, and time step $\Delta t$, on the algorithm's performance. The CD-FQA is shown to be robust across different system sizes and parameter settings, with the best performance observed for $\alpha$ values that are not too large. Additionally, the authors discuss strategies to improve the CD-FQA when it encounters convergence issues, such as using linear combinations of counterdiabatic operators or adding time-dependent terms. Finally, the CD-FQA is demonstrated on IBM's quantum computer, showing consistent energy decay and improved performance over the standard FQA. The paper concludes by highlighting the potential of the CD-FQA in advancing quantum algorithms for ground state preparation and quantum control methods.The paper introduces a novel quantum algorithm, the Counterdiabatic Feedback-Based Quantum Algorithm (CD-FQA), which integrates quantum Lyapunov control (QLC) with the counterdiabatic driving protocol. This approach aims to enhance the efficiency of preparing ground states in quantum many-body systems and solving combinatorial optimization problems. The CD-FQA algorithm is designed to accelerate population transfer to low-energy states compared to conventional feedback-based quantum algorithms, reducing the quantum circuit depth and computational resources required. The authors apply the CD-FQA to one-dimensional quantum Ising spin chains, demonstrating its effectiveness through comprehensive simulations. The algorithm's performance is compared with the standard Feedback-Based Quantum Algorithm (FQA) and classical simulations. The results show that the CD-FQA significantly reduces the time needed to reach low-energy states, with the best performance achieved using the $Y$ operator as the second control Hamiltonian. The study also explores the impact of various parameters, such as the control field strength $\alpha$, system size $N$, and time step $\Delta t$, on the algorithm's performance. The CD-FQA is shown to be robust across different system sizes and parameter settings, with the best performance observed for $\alpha$ values that are not too large. Additionally, the authors discuss strategies to improve the CD-FQA when it encounters convergence issues, such as using linear combinations of counterdiabatic operators or adding time-dependent terms. Finally, the CD-FQA is demonstrated on IBM's quantum computer, showing consistent energy decay and improved performance over the standard FQA. The paper concludes by highlighting the potential of the CD-FQA in advancing quantum algorithms for ground state preparation and quantum control methods.