Corneliu Lazar

Modelling and predictive control of an electro-hydraulic actuated wet clutch for automatic transmission

Multi-plate wet clutches and theirs actuators are an important part of the automatic transmission gearboxes. Modern electronic controls operate the clutch by an electro-hydraulic actuator. In this paper a new model for a wet clutch actuated by an electro-hydraulic valve used in a real vehicle for automatic transmission is developed. The model captures the essential dynamics of the electro-hydraulic valve and clutch circuit, which operates on a given pressure range commanded by a transmission shifting signal. The model is validated against the data obtained from a test bench which includes the DQ250 wet clutch actuated by the electro-hydraulic valve DQ500 and the comparison shows good agreement. Based on the developed model, a useful clutch prediction control scheme was designed. Simulation results obtained with predictive control strategy are presented and discussed.

Visual Servoing of Robot Manipulators Using Model-based Predictive Control

In this paper, a model predictive control strategy is presented to visual servoing a robot manipulator with eye-in-hand configuration. Starting with the discrete form of the time derivative of features related with camera velocity through image Jacobian matrix and taking into account the discrete robot model, a new approach for computing the predictions is introduced. By means of a cost function based on errors in image plane, convergence of robot motion has been obtained through nonlinear constraint optimization, which takes into consideration the visibility loss of features due to camera motion. Using a visual servoing simulator, the predictive strategy was successfully tested.

Predictive Control Architecture for Visual Servoing of Robot Manipulators

Abstract A novel architecture for integrating reference trajectory and image prediction is proposed to be used in predictive control of visual servoing systems. In the proposed method, a new predictor is developed based on the relation between the camera velocity and the time variation of the visual features given by the interaction matrix. In addition, a reference trajectory is introduced to define the way how to reach the desired features over the prediction horizon starting from the current features. Simulations reveal the efficiency of the proposed architecture to control a 6 degrees of freedom robot manipulator.

Modeling of a pressure reducing valve actuator for automotive applications

Significant research effort has been directed towards developing vehicle systems that reduce the energy consumption of an automobile and because pressure control valves are used as actuators in many control applications for automotive systems, a proper dynamic model is necessary. Starting from equations found in literature, where a single stage pressure reducing valve is modelled, in this paper, the concept of modeling a real three land three way solenoid valve actuator for the clutch system in the automatic transmission is presented. Two simulators for an input-output model and a state-space model were developed and these were validated with data provided from experiments with the real valve actuator on a test bench.

Optimal torque control of the Interior Permanent Magnet Synchronous Machine

The basic function of any type of electric machine used in automotive powertrain is to propel the automobile in motor mode or to recharge the high-voltage battery in generator mode. The torque control of electric machine in motor and generator modes, using more efficient high-voltage battery, is a goal for automotive industry. The entire control structure must be designed so as to take into account also the limitations of the computer based implementation in an Electronic Control Unit. A good choice for Hybrid Electric Vehicles (HEVs), due to many advantages, is the Interior Permanent Magnet Synchronous Machine (IPMSM). In this paper, a model for a 35 KW IPMSM used by a future HEV is presented. Starting from the developed model a dynamic simulator was implemented in MATLAB/SIMULINK and then, an optimal field oriented control strategy is applied with aims at optimum torque control both in constant torque region and in constant power region, considering the variation of machine parameters. The model was validated against the data provided by Continental Automotive Romania from the system testbench. The simulated results obtained with the proposed control strategy are compared with the ones obtained with the classical PID approach and the results show improved performances.

Real-Time Multi-Rate Predictive Cascade Speed Control of Synchronous Machines in Automotive Electrical Traction Drives

A challenging task in automotive electrical traction drives is to control the speed of synchronous machines due to the existing physical and computational constraints. The goal of this paper is to find a control solution which can answer this problem. To this end, a multirate predictive cascade speed control structure suitable for real-time implementation is proposed. The focus in this paper is only on the design of the outer-loop controller. First, a suitable mathematical model for the outer-loop plant which includes also the dynamics of the inner control loop is obtained. Second, a one-step-ahead state-feedback model predictive controller based on flexible Lyapunov function concept is employed to control the rotor electrical speed. Third, a state and disturbance observer is employed to estimate the load torque and the unmeasured state. This ensures also offset-free operation of the closed-loop system. To illustrate its effectiveness, the proposed control solution is implemented in a real microcontroller and tested in real time on an industrial hardware-in-the-loop test bench and on a real traction test bench.

Fast Real-Time Constrained Predictive Current Control in Permanent Magnet Synchronous Machine-Based Automotive Traction Drives

The current control in permanent magnet synchronous machine (PMSM) drives is a challenging problem which has to deal with physical and real-time constraints. The goal of this paper is to provide a control solution that can deal effectively with these challenges. The objective is to adjust the stator voltages to obtain fast and monotonic transient current response while satisfying the existing constraints. To this end, using the PMSM model in the rotor coordinates, an explicit one-step ahead predictive control law which uses tools from Lyapunov theory is developed. First, a polytopic approximation of the quadratic constraints is used to reduce the complexity. Then, the optimization problem is reduced to a linear program. Furthermore, a piecewise affine explicit control law is obtained via multiparametric linear programming. As a consequence, the online computation of the control law is reduced to a point location problem yielding a fast control method suitable for real-time implementation. Second, the speed-dependent terms of the mathematical model are considered as disturbance. Then, a state and disturbance observer is designed using a quadratic Lyapunov function to guarantee asymptotic stability of the estimation error. Real-time results obtained in an industrial hardware-in-the-loop test-bench are reported and analyzed.

Multivariable model-based control strategies for level control in a quadruple tank process

This paper presents three model-based control strategies applied to a multivariable process. First, a simple and rather naive approach is employed, i.e. treating the process as two SISO (Single Input Single Output) loops and design PID controllers. Obviously, this approach is effective, but does not take into account the interaction between the loops. Next, interaction is compensated by using dynamic decouplers and control performance is improved. Finally, a multivariable IMC (Internal Model Control) method is applied. All the results were validated on the laboratory setup with coupled quadruple tanks from Quanser. This is an interesting and challenging testbed for control, i.e. it poses non-minimum phase transmission zeros. Our experimental results show that the IMC outperforms the PID control at the cost of additional design complexity. All controllers were successfully tested for setpoint trajectory and disturbance rejection and tackled well the noise in the system.

Visual predictive control architecture based on image moments for manipulator robots

Increasing performances of nonlinear predictive control techniques for visual servoing systems, by using image moments as visual features, is the main goal of this paper. An local model based predictor is developed and the cost function is constructed using a image moments based reference trajectory. A new type of visual predictive control architecture is designed and a simulator is developed. Simulation results for a 6 d.o.f eye-in-hand scheme are revealed.

Image features detection using phase congruency and its application in visual servoing

Image features represent inputs for different types of visual applications. For visual servoing tasks the chosen features must be stable, accurate and robust. Gradient based algorithms for feature detection are sensitive to noise, illumination change and scale change. Using phase congruency, an image feature detection algorithm is developed based on the local energy model. The performances of the detection algorithm were tested using a simulated visual servoing architecture. Simulation was performed using an image sequence acquired by an eye-in-hand real system of a six degree of freedom robot manipulator.