Endurance and changes in electromyogram (EMG) power spectra were investigated during a fatiguing static contraction at 50% of the maximum EMG amplitude in two jaw-elevator muscles (masseter and temporalis) and five facial muscles (frontalis, corrugator supercilii, zygomaticus major, orbicularis oris, and buccinator). Relatively high endurance was found in orbicularis oris, frontalis, and corrugator supercilii muscles; intermediate endurance was found in zygomaticus major, buccinator, and temporalis muscles; and low endurance was found in the masseter muscle. The last muscle showed a relatively fast linear decrease of the median frequency of the power spectrum. The other muscles showed a much slower, exponential decrease. The median frequency appeared to reflect reliably the changes in the shape of the power spectra during fatigue. Large differences between the shape of power spectra of different muscles in the unfatigued state were found. These, however, were unrelated to endurance and degree of spectral shift during fatigue.
As a response to the ever more stringent emission standards, automotive engines have become more complex with more actuators. The traditional approach of using many single-input single output controllers has become more difficult to design, due to complex system interactions and constraints. Model predictive control offers an attractive solution to this problem because of its ability to handle multi-input multi-output systems with constraints on inputs and outputs. The application of model based predictive control to automotive engines is explored below and a multivariable engine torque and air-fuel ratio controller is described using a quasi-LPV model predictive control methodology. Compared with the traditional approach of using SISO controllers to control air fuel ratio and torque separately, an advantage is that the interactions between the air and fuel paths are handled explicitly. Furthermore, the quasi-LPV model-based approach is capable of capturing the model nonlinearities within a tractable linear structure, and it has the potential of handling hard actuator constraints. The control design approach was applied to a 2010 Chevy Equinox with a 2.4L gasoline engine and simulation results are presented. Since computational complexity has been the main limiting factor for fast real time applications of MPC, we present various simplifications to reduce computational requirements. A benchmark comparison of estimated computational speed is included.
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