This paper proposes a novel hybrid control framework by combing enhanced extended state observer with Trajectory linearization control for air vehicle acceleration tracking problems. First, based on the tracking error dynamics derived by Taylor expansion for the original nonlinear system along the desired Trajectory, a feedback linearization-based control law is designed to stabilize a linear time-varying system. To reduce the controller performance sensitivity to uncertainties, with partial model information, an enhanced extended state observer is constructed to estimate the tracking error vector, as well as the uncertainties in an integrated manner. The closed-loop stability of the system under the proposed compound scheme is established. Both numerical simulation studies and an application example of air vehicle acceleration autopilot design demonstrate the feasibility and efficacy of the proposed method.

In this paper, the purpose is spacecraft Trajectory design and correction in de-orbit maneuver. According to the ‎systematic requirements, this maneuver is required for a real project and its parameters and values have been ‎set by its system engineering team. In order to achieve the desired maneuver, propulsion system must produce ‎the velocity change vector. In practice, due to the unsatisfactory performance and uncertainties in the ‎propulsion system, ideal velocity change vector may not be realized. Consequently, spacecraft deviates from ‎the desired de-orbit Trajectory and it is possible the spacecraft mission fails. So as to avoid this problem and ‎compensate the created deviation, a controller based on Cowell’s formulation and using feedback linearization ‎method is designed and its performance, after generating and loading desired de-orbit Trajectory in the control ‎law (using the orbital elements), will be examined during a de-orbit maneuver. In this article, for a considered ‎impulsive de-orbit maneuver, velocity change vector and its execution time which are necessary for transfer ‎from initial orbit to the de-orbit Trajectory, are calculated. The simulation results indicate that, due to technical ‎constraints and the capacity of the propulsion system, the maximum error of de-boost impulse value and ‎orientation which the controller can compensate are 15% and 20% respectively.

This paper proposes a guidance law design for Trajectory tracking of a leader UAV and formation flight of pursuer UAVs. According to nonlinear kinematics for both problems, the feedback linearization theory has ben used. Therefore, using this theory, the nonlinear problem has been transferred to a linear one and using the linear control theory the control parameters has been determined to achieve the desired performance. In the Trajectory tracking problem, assuming a constant velocity leader, a change of the independent variable from the time to the downrange has been performed and the problem is transferred to a single-input single-output control problem, consequently, the controller is designed. In the formation flight problem, assuming pursuers with the bounded controllable velocity, we have a two-input two-output nonlinear system. Supposing no communications between pursuers and the leader, a second order sliding mode observer is utilized to estimate the required states in formation flight controller. Results show that the settling time of Trajectory tracking error of the proposed nonlinear guidance law is almost 30% better than the nonlinear Trajectory tracking controller based on the proportional navigation guidance law. Also, the designed formation flight has a good performance in controlling the formation flight. Also, the sliding mode observer is able to estimate the leader states even in the presence of noise.

pH control is a challenging problem due to its highly nonlinear nature. In this paper the performances of two different adaptive global linearizing controllers (GLC) are compared. Least squares technique has been used for identifying the titration curve. The first controller is a standard GLC based on material balances of each species. For implementation of this controller a nonlinear state estimator is used. Some modifications are proposed to avoid the singularity of the observer gain. The second controller is designed based on the reduced state equation. Through computer simulations, it has been shown that the performances of the second GLC is superior and it is more robust to process model mismatch. It should be also noted that the design of reduced state-based GLC is much easier and dose not need observer for implementation.

Distillation column control has been a challenging problem for numerous research activities. Review of past research reveals that among the advanced control methods applied to this system, little attention has been paid to feedback linearization, even in absolutely theoretical cases. This is due to the singularity of the system in steady-state, which invalidates the linearized control law. In this paper, to overcome this problem, a new idea has been suggested that is based on approximate feedback linearization. Based on this idea, an approximate non-linear model has been introduced for the distillation column which can exactly be linearized while reserving the structural properties of the basic system. The control law is derived from the approximate model and then applied to the basic system. The introduced error between the approximate and basic systems is then fed back by two single loop PID controllers to improve the performance of the system. Further, in these approach disturbances due to changes of feed flow and composition has been perfectly decoupled using the disturbance decoupling theory.