Powered knee prostheses, compared to traditional energetically-passive knee prostheses, greatly enhance the mobility of transfemoral amputees. However, powered prostheses have a large number of control parameters that must be adjusted for individual amputee users, which presents a great challenge for clinical use. To address this challenge, we proposed and compared 2 automatic tuning strategies (i.e. parallel and sequential) using our newly developed optimal adaptive dynamic programming (ADP) tuner that objectively tuned the control parameters of an experimental powered knee prosthesis to mimic the knee profile of an able-bodied person (i.e. reference profile). With the parallel tuning strategy, we tuned all control parameters during the stance and the swing phases simultaneously. With the sequential tuning strategy, we alternately tuned stance or swing phase control parameters while fixing the remaining parameters. One able-bodied subject with a prosthesis adapter and one transfemoral amputee subject walked with the experimental powered knee prosthesis under both tuning strategies. Results show that with both tuning strategies, the ADP tuner successfully tuned the impedance parameters to match the prosthetic knee profile to the reference profile. Additionally, the parallel strategy outperformed the sequential strategy with better convergence to the reference profile. Interestingly, with the sequential tuning strategy, tuning during the swing phase greatly impacted the subsequent stance phase profile, but the impact was not as great when the order of tuning was switched. The ability to simultaneously adjust all control parameters with ADP using a parallel strategy may be a preferred solution for the current high-dimension control challenge, which may lead to more advanced, adaptive powered knee prostheses.