A Novel Working Point Control Method with Solving the Nonlinear Control Problem of I-V Outer-loop for Space Solar Array Simulator

Author(s):  
Shanshan Jin ◽  
Donglai Zhang ◽  
Zicai Wang ◽  
Hua Zhang
2013 ◽  
Vol 2013 ◽  
pp. 1-16 ◽  
Author(s):  
Dictino Chaos ◽  
David Moreno-Salinas ◽  
Rocío Muñoz-Mansilla ◽  
Joaquín Aranda

This work studies the problem of trajectory tracking for an underactuated RC-hovercraft, the control of which must be done by means of discrete inputs. Thus, the aim is to control a vehicle with very simple propellers that produce only a discrete set of control commands, and with minimal information about the dynamics of the actuators. The control problem is approached as a cascade control problem, where the outer loop stabilizes the position error, and the inner loop stabilizes the orientation of the vehicle. Stability of the controller is theoretically demonstrated and the robustness of the control law against disturbances and noise is established. Simulation examples and experiments on a real setup validate the control law showing the real system to be robust against disturbances, noise, and outdated dynamics.


2009 ◽  
Vol 45 (1) ◽  
pp. 96-104
Author(s):  
R. Gabasov ◽  
F. M. Kirillova ◽  
E. A. Ruzhitskaya

2011 ◽  
Vol 317-319 ◽  
pp. 1373-1384 ◽  
Author(s):  
Juan Chen ◽  
Chang Liang Yuan

To solve the traffic congestion control problem on oversaturated network, the total delay is classified into two parts: the feeding delay and the non-feeding delay, and the control problem is formulated as a conflicted multi-objective control problem. The simultaneous control of multiple objectives is different from single objective control in that there is no unique solution to multi-objective control problems(MOPs). Multi-objective control usually involves many conflicting and incompatible objectives, therefore, a set of optimal trade-off solutions known as the Pareto-optimal solutions is required. Based on this background, a modified compatible control algorithm(MOCC) hunting for suboptimal and feasible region as the control aim rather than precise optimal point is proposed in this paper to solve the conflicted oversaturated traffic network control problem. Since it is impossible to avoid the inaccurate system model and input disturbance, the controller of the proposed multi-objective compatible control strategy is designed based on feedback control structure. Besides, considering the difference between control problem and optimization problem, user's preference are incorporated into multi-objective compatible control algorithm to guide the search direction. The proposed preference based compatible optimization control algorithm(PMOCC) is used to solve the oversaturated traffic network control problem in a core area of eleven junctions under the simulation environment. It is proved that the proposed compatible optimization control algorithm can handle the oversaturated traffic network control problem effectively than the fixed time control method.


2013 ◽  
Vol 860-863 ◽  
pp. 1073-1077 ◽  
Author(s):  
Zhi Guo Kong ◽  
Hong Wei Zhang ◽  
Zi Ning Tang

In order to improve the performance of a new type of full hybrid electric bus, this paper puts forward a set of coordinated control method to adjust the operation of the engine and two motors. In the engine start-stop logic control, comprehensive consideration of SOC, the speed of the bus and the accelerator pedal stroke are performed, while hysteresis control is introduced to improve the stability of the control; In the engine working point adjusting control, not only the engine speed command rate of change was optimized, but also the output torque rate was optimized to match the air injection and exhaust, etc. Further, the method based on dynamic constraints was used to optimize the working point adjustment process. At present, there are hundreds of busses operates in route. Results verify the feasibility and effectiveness of the control method. The vehicle has good fuel economy, and the dynamic performance and driving comfort are also greatly improved.


Sensors ◽  
2017 ◽  
Vol 17 (9) ◽  
pp. 2147 ◽  
Author(s):  
Dunzhu Xia ◽  
Limei Cheng ◽  
Yanhong Yao

2006 ◽  
Author(s):  
William S. Oates ◽  
Phillip Evans ◽  
Ralph C. Smith ◽  
Marcelo J. Dapino

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